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NewNeurIPS 2026OralsSpotlightsPostersWhat's worth reading in RL this week?Most debated papers this monthWho's working on agent memory?What's new in diffusion models?
Paper of the day91%Must readDoes Learning Protein Folding Generalize to Broader Reasoning?Fold2Reason delivers a verified 3.23-point reasoning gain and rigorous geometry controls, but its broad reasoning claims remain fragile against 3D pattern-matching critiques and thin benchmark margins.

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78%Program-as-Weights: A Programming Paradigm for Fuzzy FunctionsProgram-as-Weights compiles natural-language specs into compact local neural adapters that match large-model prompting with far less memory and faster offline execution.NeurIPS 2026Highly rated · ▲ 307 on HF · 6 comments
91%Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End LatencyLoHi trades per-frame resolution for denser temporal sampling via low-resolution streams plus sparse high-resolution frames, boosting long-video accuracy up to 10.6 points and cutting front-end latency up to 7x.NeurIPS 2026Must read · ▲ 13 on HF · 18 comments
86%Recursive Multi-Agent SystemsRecursiveMAS scales multi-agent collaboration through recursive latent-space computation via RecursiveLink and inner-outer loop co-optimization, improving accuracy by 8.3% with 1.2-2.4x speedup and 34.6%-75.6% token reduction over baselines.NeurIPS 2026Must read · ▲ 239 on HF · 6 comments
88%PaLoRA: Paced Low-Rank Adaptation for Continual LearningPaLoRA derives an optimal rank-aware pacing law for LoRA continual learning that adaptively restricts gradient scaling to prevent forgetting, improving long-horizon benchmark accuracy by 4%.NeurIPS 2026Must read · ▲ 9 on HF · 17 comments
78%Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before AnsweringImagine3D-LLM learns compact scene representations via learnable summary tokens decoded into 3D Gaussian splatting with photometric loss, improving multi-view spatial reasoning benchmarks.NeurIPS 2026Highly rated · ▲ 72 on HF · 14 comments
76%Learning from the Self-future: On-policy Self-distillation for dLLMsd-OPSD applies on-policy self-distillation to diffusion LLMs via suffix conditioning and step-level supervision, cutting optimization steps by ~90% versus RLVR while outperforming baselines on reasoning benchmarks.NeurIPS 2026Highly rated · ▲ 174 on HF · 4 comments
73%AgentGrad: Intervention-guided Prompt Optimization for Multi Agent SystemsAgentGrad improves multi-agent prompt optimization via sequential intervention and semantic gradient clustering, achieving state-of-the-art performance with 2.5x faster optimization and 21.8% lower cost.NeurIPS 2026Highly rated · 0% of 1 readers upvoted · ▲ 107 on HF · 5 comments
84%DynamicVLA: A Vision-Language-Action Model for Dynamic Object ManipulationDynamicVLA combines efficient inference with continuous action streaming to fix latency-induced mismatches, improving dynamic manipulation success across synthetic and real-world benchmarks.NeurIPS 2026Must read · 100% of 1 readers upvoted · ▲ 77 on HF · 6 comments
88%MulTaBench: Benchmarking Multimodal Tabular Learning with Text and ImageMulTaBench benchmarks 40 multimodal tabular datasets and shows target-aware tuning of text and image embeddings improves predictive performance over frozen embeddings.NeurIPS 2026 SpotlightMust read · ▲ 142 on HF · 4 comments
76%Self-Distilled RLVRRLSD combines RLVR and self-distillation, using token-level policy differences for update magnitudes and environmental feedback for directions, improving convergence and stability.NeurIPS 2026 SpotlightHighly rated · ▲ 145 on HF · 4 comments
75%MiroEval: Benchmarking Multimodal Deep Research Agents in Process and OutcomeMiroEval benchmarks multimodal deep research agents via process and outcome evaluation across 100 real-world tasks, finding process quality predicts outcomes and multimodal tasks reduce scores by 3, 10 points.NeurIPS 2026Highly rated · 0% of 1 readers upvoted · ▲ 69 on HF · 6 comments
90%A Matter of TASTE: Improving Coverage and Difficulty of Agent BenchmarksTASTE reverses benchmark construction by evolving tool sequences to automatically generate harder, broader-coverage agent tasks that expose severe performance drops and saturation in existing benchmarks.NeurIPS 2026Must read · 100% of 1 readers upvoted · ▲ 74 on HF · 5 comments
91%?CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation ModelsCollabVR pairs vision-language models with video generation models in closed-loop step-level planning and verification, reducing drift and simulation errors for major video reasoning gains.NeurIPS 2026Must read · 100% of 1 readers upvoted · vote to see score · ▲ 71 on HF · 5 comments
82%?Optimal Transport Reweighting for Robust Learning under Spurious Correlations and Label NoisePOTER uses optimal transport geometry between training and reference distributions to downweight mislabeled or shortcut-aligned samples, achieving state-of-the-art worst-group accuracy with a single training stage.NeurIPS 2026Must read · 100% of 1 readers upvoted · vote to see score · 8 comments
86%?Code2World: A GUI World Model via Renderable Code GenerationCode2World uses renderable code generation for GUI world modeling, achieving top next-UI prediction and boosting Android navigation success by up to 9.5%.NeurIPS 2026Must read · vote to see score · ▲ 186 on HF
76%?Heterogeneous Agent Collaborative Reinforcement LearningHACRL enables heterogeneous agents to share verified rollouts during collaborative on-policy training and execute independently at inference, with HACPO improving all agents by 3.6% over baselines at half the rollout cost.NeurIPS 2026Highly rated · vote to see score · ▲ 110 on HF · 4 comments
Representation & contrastive learning73%?Structure-agnostic Causal Representation LearningSaCRL jointly identifies causal structure and learns invariant representations via soft optimization over HSIC-based invariance violations without prior structural knowledge. It guarantees structure identification, invariance satisfaction, and out-of-distribution generalization while achieving stateNeurIPS 2026Highly rated · 0% of 1 readers upvoted · vote to see score · 8 comments
91%?Claw-Eval: Towards Trustworthy Evaluation of Autonomous AgentsClaw-Eval introduces a trajectory-aware benchmark with 300 tasks, finding opaque grading misses 44% of safety violations and agent rankings vary across multi-dimensional capabilities.NeurIPS 2026Must read · vote to see score · ▲ 117 on HF · 3 comments
90%?Modeling quantum neural network gradient with reinforcement learningRLQ-Grad uses reinforcement learning to propose quantum neural network updates without differentiating circuits, avoiding barren plateaus and scaling with parameters rather than Hilbert space dimension to achieve orders-of-magnitude faster training and higher accuracy.NeurIPS 2026Must read · 100% of 1 readers upvoted · vote to see score · 6 comments
78%?Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and GenerationTuna-2 replaces vision encoders with patch embeddings for end-to-end pixel-space multimodal understanding and generation, achieving state-of-the-art results that outperform encoder-based designs at scale.NeurIPS 2026Highly rated · vote to see score · ▲ 70 on HF · 4 comments
89%?Principia: Relational Physics Tests for Video ModelsPrincipia benchmarks video generators via calibration-independent relational physics consistency across eight Newtonian phenomena, finding top models score below 0.42 despite high VBench ratings.NeurIPS 2026Must read · vote to see score · ▲ 18 on HF · 6 comments
91%?Jointly Reinforcing Diversity and Quality in Language Model GenerationsDARLING uses a learned partition function to jointly optimize language model response quality and semantic diversity via reinforcement learning, improving both quality and novelty across creative and math benchmarks.NeurIPS 2026Must read · vote to see score · ▲ 25 on HF · 5 comments
89%?Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus InteractionDirect corpus interaction uses terminal tools to search raw corpora directly, bypassing fixed retrieval interfaces and substantially outperforming sparse, dense, and reranking baselines on agentic search benchmarks.NeurIPS 2026 SpotlightMust read · vote to see score · ▲ 125 on HF
83%?TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route GenerationTransitLM provides 13 million transit records to train LLMs for map-free route generation, yielding accurate routes that implicitly ground GPS coordinates without maps.NeurIPS 2026Must read · vote to see score · ▲ 127 on HF

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91%DEPICT: Scoring Text-to-Image Alignment by Answer AgreementDEPICT scores text-to-image alignment via expected agreement between image and caption answers, boosting negation accuracy to 88% and exceeding fine-tuned evaluators on human correlation benchmarks.Must read · ▲ 3 on HF · 6 comments
91%Dataset Identity, Not Novelty: The Source of an Inflated OOD Detection GainPost-hoc OOD detectors inflate reported gains by fitting dataset identity rather than novelty, leaving only a single constant fit valid.Must read · 3 comments
91%Does Learning Protein Folding Generalize to Broader Reasoning?Post-training on protein-folding data via discrete answers and continuous geometry improves structure prediction and broad reasoning across ten benchmarks.Must read · 100% of 1 readers upvoted · ▲ 120 on HF · 5 comments
91%HuatuoGPT-3: RL-Only Domain Adaptation from Base ModelsOnePO enables RL-only medical domain adaptation via adaptive objective evolution and teacher retirement, yielding HuatuoGPT-3 that surpasses frontier models.ICML 2026Must read · 100% of 1 readers upvoted · ▲ 15 on HF · 4 comments
91%OSWorld-Pro: Process-based Evaluation for Computer Use AgentsOSWorld-Pro introduces process-based evaluation with 2,800 subgoals across 300 tasks, revealing top models achieve only 75.7% subgoal success versus 83.4% end-state performance and identifying distinct failure modes like irrelevant actions and click errors.Must read · 100% of 1 readers upvoted · ▲ 15 on HF · 6 comments
LLM agents & planning91%StateM: Reaching 95.3% Raw Accuracy, or a \$15 Frontier Run, on Terminal-Bench 2.1 via Harness ScalingStateM improves long-horizon agent accuracy via durable-state harness scaling without model changes, reaching 95.3% on Terminal-Bench 2.1 and cutting API costs to about $15 versus $574.68.Must read · ▲ 452 on HF · 11 comments
91%DeskForge: Dense Supervision from Desktop Environments for Computer-Use AgentsDeskForge generates dense desktop supervision via controllable real-app environments, yielding 1.2M observations that improve GUI grounding and long-horizon computer-use task completion.Must read · ▲ 10 on HF · 5 comments
91%Sharpening Tax in Post-TrainingPost-training sharpens base model behaviors at the cost of solution coverage, introducing a quantifiable "Sharpening Tax"; a posterior-tempered group sampler reduces this tax while boosting accuracy.Must read · ▲ 102 on HF · 4 comments
91%False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search AgentsSelf-evolving search agents suffer co-cheating where proposers and solvers mutually reinforce errors; CrossFit partitions sources to cross-fit agreement and cuts false agreement by over half, boosting downstream search by 8+ points.Must read · ▲ 670 on HF · 5 comments
91%Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End LatencyLoHi trades per-frame resolution for denser temporal sampling via low-resolution streams plus sparse high-resolution frames, boosting long-video accuracy up to 10.6 points and cutting front-end latency up to 7x.NeurIPS 2026Must read · ▲ 13 on HF · 18 comments
91%UndoBench: Separating Task Competence from Recovery Capability in Tool-Using AI AgentsUndoBench separates tool-using agent competence from fault recovery via paired enterprise workflow trials, finding 83.54% nominal success but only 46.72% recovery success with phase-dependent vulnerabilities.Must read · ▲ 11 on HF · 16 comments
91%Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social DisseminationThe RA-Bench benchmark reveals current detectors fail to consistently identify AI-generated crisis videos, which become harder to detect after social dissemination and frequently mislead humans.Must read · ▲ 287 on HF · 15 comments
91%?CurveCodec 2: Skeleton-agnostic animation compression with a learned entropy modelCurveCodec 2 predicts quantized skeletal curves from past values and learns residual entropy models to reduce animation storage to 0.22-0.37x of ACL with verified error bounds.Must read · vote to see score · ▲ 4 on HF · 16 comments
91%?Where Does Retrieval-Based Open-Ended Evaluation Fail? Automatic Taxonomy Induction from Long-Form Medical Answer Factuality VerificationAutomatic taxonomies reveal retrieval and verifier reasoning failures persist across scaled medical retrieve-then-verify systems, showing fundamental open-ended evaluation limits.Must read · vote to see score · ▲ 12 on HF · 4 comments
91%?OpenART: Scaling Agent Red Teaming via Open-Ended Environment EvolutionOpenART scales agent red teaming via open-ended environment evolution across 10,000 stateful scenarios, with EMHA achieving 85% attack success that grows with complexity.Must read · vote to see score · ▲ 266 on HF · 6 comments
91%?Learning Functional Subspaces for Neural Network CompressionLSP learns low-rank subspaces end-to-end via joint orthogonal projector optimization to reduce transformer memory and compute while outperforming local criteria at high compression ratios.Must read · vote to see score · ▲ 1 on HF · 4 comments
91%?QuantWM: Temporally Consistent 2-Bit KV Cache Quantization for Video World ModelsQuantWM is a training-free 2-bit KV cache quantization framework for video world models that preserves attention logits and token selection to eliminate temporal flickering while achieving up to 6.20x memory compression.Must read · vote to see score · ▲ 13 on HF · 3 comments
90%?World Action Learning via Interaction-Centric Spectral Latent GuidanceWING distills interaction-centric latent actions from egocentric video and uses cross-embodiment spectral low-frequency guidance to transfer them to robot policies, achieving high success rates on LIBERO, RoboTwin, RoboCasa, and real-world tasks.Must read · 100% of 1 readers upvoted · vote to see score · ▲ 20 on HF · 4 comments
90%?From Evidence to Action: How Tool-Using Agents FailTool-using agents often fail by acting before establishing required evidence or leaving multi-action workflow prerequisites unresolved, despite accurate static action assessment. SafeActBench reveals failures stem from how agents use established evidence during execution, not just missing informatioMust read · 100% of 1 readers upvoted · vote to see score · ▲ 20 on HF · 3 comments
90%?World Models' Last Exam in PhysicsWorld Models' Last Exam in Physics benchmarks video models via 40 measurement-based physics tasks, finding the best model scores 57.76/100 with widespread inconsistencies.Must read · 100% of 1 readers upvoted · vote to see score · ▲ 2 on HF · 4 comments
89%?PointWAM: 3D World Action Modeling for Dexterous Robotic ManipulationPointWAM forecasts 3D point trajectories of scenes and hands in a shared space-time frame to guide dexterous robot manipulation, improving DexJoCo success by 56.9 points with video pre-training.Must read · vote to see score · ▲ 42 on HF · 6 comments
89%?AGO AI Quality Gate: Evidence-First Release Decisions for Retrieval-Augmented GenerationAGO is an evidence-first quality gate for RAG that treats judge errors and missing data as explicit outcomes, using stratified beta-binomial gates and mandatory meta-evaluation to reduce unsafe promotion to 22.2%-35.1% versus 29.3%-41.8% for naive gates.Must read · vote to see score · ▲ 13 on HF · 5 comments
89%?PDE-JEPA: Predictive Representation Learning of Latent Dynamics Modeling for Parametric PDEsPDE-JEPA introduces predictive masked-latent pretraining with geometry projection and structured latent predictors for parametric PDE dynamics, reducing errors by 33.4% in-distribution and 51.4% on unseen parameters.Must read · vote to see score · ▲ 53 on HF · 6 comments
89%?MM-ABC: Towards Generalist Mobile Manipulation via Seeing, Coordinating and ImaginingMM-ABC is a mobile manipulation foundation model combining multi-level vision features, future imagination supervision, and masked joint attention to coordinate arm-base actions, achieving up to 99.1% success across benchmarks and 83% in real-world tasks.Must read · vote to see score · ▲ 5 on HF · 6 comments

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86%Thinking with Video: Video Generation as a Promising Multimodal Reasoning ParadigmVideo generation enables unified multimodal reasoning via Sora-2, which matches vision-language models and exceeds GPT-5 on spatial tasks while scoring 92% on MATH.Must read · ▲ 242 on HF · 22 comments
83%The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy DistillationRIDE extrapolates RL-induced representation residuals for stable on-policy distillation, surpassing output-space methods and matching or exceeding RL teachers.Must read · ▲ 577 on HF · 19 comments
86%Adaptive Fused Prior Transfer for Controllable Generative Image CompressionAFP-GIC transfers adaptive fused priors from a frozen pretrained model to guide generative compression without transmitting them, reducing decoder latency and parameters while improving very-low-bitrate naturalness.Must read · ▲ 4 on HF · 18 comments
76%Adapting prior-data fitted networks for tabular anomaly detectionFrozen and fine-tuned TabPFN representations for tabular anomaly detection yield ZEN and FOCUS, surpassing all ADBench baselines in AUROC despite unsupervised deployment and contaminated reference sets.ICLR 2027Highly rated · ▲ 5 on HF · 18 comments
89%Sharpen Without Search: On-Policy Distillation of Sequence-Level Power DistributionOn-policy power distillation trains models to generate sharpened answers directly, improving single-sample math reasoning by up to 27.3 points and outperforming multi-candidate sampling and reward-based methods.Must read · ▲ 4 on HF · 18 comments
89%Certification of Real Images through Calibrated Content AuthenticationDeepfake detectors degrade to 76% accuracy and near-zero under attacks, so calibrated reconstruction-based authentication bounds false real-image certification to 1%.Must read · ▲ 13 on HF · 18 comments
91%Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End LatencyLoHi trades per-frame resolution for denser temporal sampling via low-resolution streams plus sparse high-resolution frames, boosting long-video accuracy up to 10.6 points and cutting front-end latency up to 7x.NeurIPS 2026Must read · ▲ 13 on HF · 18 comments
83%PerturBot: Breaking Shortcut Priors in Vision-Language-Action Models with Perturbative TrainingPerturbBot breaks vision-language-action shortcut priors via perturbative training while GroundingFscore diagnoses shortcut reliance, enabling healthier scaling without altering inference.Must read · ▲ 13 on HF · 17 comments
67%Collaborative Personalized Preference Alignment for LLMs under Data DeficiencyAPO learns shared LLM aligner initializations via grouped gradient coordination to enable few-shot personalization under heterogeneous preferences and scarce feedback, improving over baselines with 20 local examples.Highly rated · 0% of 1 readers upvoted · ▲ 5 on HF · 17 comments
71%Code2Games: Enabling Coding Agents for Gaming World GenerationCode2Games coordinates scene analysis and gameplay planning via shared representations to generate consistent gaming worlds and adapt them to Unreal Engine 5. The framework improves visual quality, interactive fidelity, and playable-game quality over direct coding-agent generation on the GameCode4D Highly rated · ▲ 6 on HF · 17 comments
88%PaLoRA: Paced Low-Rank Adaptation for Continual LearningPaLoRA derives an optimal rank-aware pacing law for LoRA continual learning that adaptively restricts gradient scaling to prevent forgetting, improving long-horizon benchmark accuracy by 4%.NeurIPS 2026Must read · ▲ 9 on HF · 17 comments
71%RealtimeWAM: One-Step Asynchronous World Action ModelsRealtimeWAM uses teacher-anchored consistency distillation and cross-expert wavefront pipelining for one-step asynchronous action generation, achieving near-lossless performance with ~25x speedup.Highly rated · 0% of 1 readers upvoted · ▲ 12 on HF · 17 comments
80%?Learning Latent Protein Languages for Autoregressive GenerationLearned latent protein languages improve autoregressive generation scaling, speed, and quality versus amino-acid and coordinate token models.Must read · vote to see score · ▲ 5 on HF · 17 comments
91%UndoBench: Separating Task Competence from Recovery Capability in Tool-Using AI AgentsUndoBench separates tool-using agent competence from fault recovery via paired enterprise workflow trials, finding 83.54% nominal success but only 46.72% recovery success with phase-dependent vulnerabilities.Must read · ▲ 11 on HF · 16 comments
86%?Training Numerical Intelligence via Auto-Diagnosis and Skill DiscoveryADSD links numerical diagnosis to reusable solver self-improvement, reducing mean solver error by nearly 71x across four challenging numerical domains.Must read · vote to see score · ▲ 8 on HF · 16 comments
86%?Learning Steadily: Accumulating Relative Point Margin Scores for Face Image Quality AssessmentCARPM-FIQA accumulates relative point margin scores across training epochs to stabilize face image quality estimates, reducing variance and improving ranking stability near top performance.Must read · 100% of 1 readers upvoted · vote to see score · ▲ 6 on HF · 16 comments
91%?CurveCodec 2: Skeleton-agnostic animation compression with a learned entropy modelCurveCodec 2 predicts quantized skeletal curves from past values and learns residual entropy models to reduce animation storage to 0.22-0.37x of ACL with verified error bounds.Must read · vote to see score · ▲ 4 on HF · 16 comments
88%?FairRSFM: A Biome-Aware Benchmark and Debiasing Framework for Remote Sensing Foundation ModelsFairRSFM benchmarks remote sensing foundation models by biome to expose hidden ecological performance disparities and tests debiasing methods without backbone updates. Aggregate metrics consistently mask large biome-dependent gaps, though mitigation effectiveness varies by model and task.Must read · vote to see score · ▲ 5 on HF · 16 comments
78%?Agentic discovery of blood biomarker from distilled private health recordsDistilling private health records into a released scoring tool enables agentic discovery of CBC biomarkers that improve diagnostic AUC over literature baselines without exposing patient data.Highly rated · vote to see score · ▲ 4 on HF · 16 comments
76%?SEER: Self-Evolving Event Reasoning and Retrieval for Time Series ForecastingSEER uses self-evolving event reasoning and retrieval to dynamically optimize forecasting with exogenous events via reflective memory and causal knowledge, outperforming state-of-the-art baselines.Highly rated · vote to see score · ▲ 13 on HF · 16 comments
88%?Periscope: Extending Frozen Language Models Beyond Their Context WindowPeriscope arranges text chunks in a grid to build an evidence map via local and strided probes, letting frozen language models answer questions across multi-million-token contexts with sublinear cost and small GPU memory.Must read · 100% of 1 readers upvoted · vote to see score · ▲ 8 on HF · 16 comments
59%?Empirical Variational AutoencoderEmpirical Variational Autoencoder learns autoregressive latent priors empirically via one linear layer to close the VAE prior-posterior gap, yielding high-fidelity sequential generation competitive with diffusion models at much faster inference.Worth a look · 0% of 1 readers upvoted · vote to see score · ▲ 7 on HF · 15 comments
89%?HLA-WM: Hybrid Linear Attention for Long-Horizon Video World ModelsHLA-WM combines geometry-guided retrieval with recurrent linear attention to fix long-range forgetting in video world models, improving 60-second consistency metrics by up to 28.5% with 12× lower memory and no retraining.Must read · vote to see score · ▲ 6 on HF · 15 comments
88%?UnAct: Gradient-Free Unlearning via Targeted Activation InterventionUnAct uses gradient-free targeted activation interventions to unlearn model classes from few forget images without gradients, labels, or retained data, matching or exceeding SSD and LFSSD accuracy across datasets and preventing network collapse with scarce data.Must read · vote to see score · ▲ 4 on HF · 15 comments

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PreprintU ZurichU PalermoUniversitat Pompeu FabraInstitut de Biologia EvolutivaBarcelona School of EconomicsGenomics & single-cell

Agta hunter-gatherer oral microbiomes are shaped by contact network structure

Agta hunter-gatherer oral microbiomes resemble Central African foragers more than neighbors, with contact networks predicting bacterial transmission and central individuals as supersharers.

Federico Musciotto, Begoña Dobón, Michael John Greenacre, Álex Mira and 12 more

Published Dec 31, 2030 · 0 citations

100% Readers1 of 1 upvoted
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arXivEmbodied agents

Attacca: Goal-Directed Control under State Continuity for Long-Horizon Embodied Agents

Attacca trains visual goal-conditioned policies on complete search-to-interact trajectories with decoupled goal images and behavioral-phase conditioning to improve long-horizon embodied task success by up to 7x.

Gyusik Seo, Jaehong Yoon

Published Oct 6, 2026 · ▲ 3 on Hugging Face · Code ★ 3

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arXivRetrieval-augmented generation

UNREAL: Unifying Retrieval and Long-Context with a Single Model

UNREAL unifies retrieval and long-context evidence selection via frozen LLM representations with minimal parameters, outperforming state-of-the-art retrievers and improving long-context accuracy substantially.

Edan Kinderman, Elad Hoffer, Yochai Blau, Brian Chmiel and 3 more

Published Oct 6, 2026 · ▲ 15 on Hugging Face

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arXivUnified multimodal models

Sensor-Language-Action Models

Sensor-Language-Action modeling unifies multimodal sensors, language, and actions via a semantic interface, and OpenSLA achieves superior hierarchical prediction and explanation with zero-shot generalization.

Yuekai Xu, Zitao Shuai, Yuzhe Yang

Published Oct 6, 2026 · ▲ 1 on Hugging Face · Code ★ 1

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arXivVideo generation

World Models' Last Exam in Physics

World Models' Last Exam in Physics benchmarks video models via 40 measurement-based physics tasks, finding the best model scores 57.76/100 with widespread inconsistencies.

Mingju Gao, Qingle Liu, Yuzhao Peng, Xinjie Lin and 7 more

Published Oct 6, 2026 · ▲ 2 on Hugging Face

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arXivEmbodied agents

VeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning

VeriFine co-evolves policies, curricula, and judges via adaptive diagnosis and coactive calibration to sustain embodied reasoning self-improvement. Experiments on driving and navigation show continuous gains in both policy and judge capability.

Zewei Zhou, Rachel Luo, Yulong Cao, Chaowei Xiao and 9 more

Published Oct 6, 2026 · ▲ 4 on Hugging Face

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arXivControllable generation

CtrlCache: Accelerating Interactive Video World Models with Control-Aware Caching

CtrlCache accelerates interactive video world models via control-aware caching that detects action changes to reuse transformer residuals and apply frequency-mixed history guidance, achieving up to 1.41x speedups with improved quality.

Shangye Song, Dong Gong, Hong Jia, Yun Sing Koh and 1 more

Published Oct 6, 2026 · ▲ 1 on Hugging Face · Code

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arXivAgent benchmarks & environments

CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?

CheckerBench evaluates long-horizon agents on synthesizing static-analysis checkers across 300 CVE-derived tasks, finding best Pass@1 reaches 45.33%.

Hang He, Li Wang, Hao Chen, Yuchen Shao and 8 more

Published Oct 6, 2026 · ▲ 52 on Hugging Face · Code

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arXivRL for LLMs

Sherpa: Teaching LLMs to Teach Adaptively

Sherpa uses multi-turn reinforcement learning to train LLM teachers that adapt instructions to diverse student archetypes, improving student performance by 20.5 points and pedagogy scores to 79.2%.

Weixian Xu, Yanzhe Zhang, Zora Zhiruo Wang, Changyu Chen and 1 more

Published Oct 6, 2026 · ▲ 3 on Hugging Face · Code

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arXivRL for LLMs

TRACE: Rollout-Guided Quantization-Aware Training for FP4 Reinforcement Learning of MoE Language Models

TRACE aligns FP4 quantization between RL training and rollout paths via rollout-guided quantization-aware training for MoE language models, achieving BF16-comparable RL performance with up to 5.4x rollout speedup.

Xin Wang, Hao Yu, Zhengyang Zhuge, Bochao Mao and 8 more

Published Oct 6, 2026 · ▲ 15 on Hugging Face

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arXivTool use & function calling

From Evidence to Action: How Tool-Using Agents Fail

Tool-using agents often fail by acting before establishing required evidence or leaving multi-action workflow prerequisites unresolved, despite accurate static action assessment. SafeActBench reveals failures stem from how agents use established evidence during execution, not just missing informatio

Hongzhan Lin, Shidong Cao, Ziyang Luo, Wenhao Chai and 2 more

Published Oct 6, 2026 · ▲ 20 on Hugging Face · Code ★ 3

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86%Must read
arXivAlignment & preference optimization

Rethinking Cross-Tokenizer On-Policy Distillation: From Alignment Coverage to Supervision Reliability

Cross-tokenizer on-policy distillation achieves comparable accuracy with strict top-16 shared-vocabulary supervision versus full coverage, while expanded span supervision reduces accuracy due to conflicting gradients, motivating prioritization of supervision reliability over alignment coverage.

Bingxi Hou, Guochao Jiang, Guofeng Quan, Weiqing Li and 3 more

Published Oct 6, 2026 · ▲ 40 on Hugging Face

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arXivAgent memory

DAEDALUS: Bootstrapping Agent Memory from Self-Generated Tasks

DAEDALUS bootstraps reusable agent memory from self-generated practice tasks without oracles, improving success rates by up to 15.9 points across benchmarks.

Antoine Edy, Max Conti, Victor Xing, Marc-Antoine Allard and 2 more

Published Oct 6, 2026 · ▲ 5 on Hugging Face · Code

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arXiv3D generation

Building Rome from a Single Image

A redesigned object-centric generator partitions scenes into distance-adaptive chunks, captures 2D-3D correspondence, and trains on 4,000 outdoor scenes to outperform baselines in indoor and outdoor mesh generation.

Jiraphon Yenphraphai, Fang Li, Tianshuo Xu, Depu Meng and 4 more

Published Oct 6, 2026 · ▲ 4 on Hugging Face

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arXivTest-time compute

Towards In-Parameter Memory Augmentation for Large Language Models

This survey organizes in-parameter memory augmentation for LLMs by parameter placement and acquisition time to enable reusable parametric knowledge at deployment.

Haoyu Huang, Zhongwei Xie, Jiaxin Bai, Yisen Gao and 5 more

Published Oct 6, 2026 · ▲ 5 on Hugging Face · Code ★ 1

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arXivRecommender systems

Personal-Agent Mediated Recommendation with Cross-Platform User History

Personal-agent mediated recommendation balances cross-platform user history against platform rankings via the MediateRec benchmark and PAMO optimization to improve rescue-harm trade-offs.

Yu Xia, Jiangfan Zhang, Jun Xiao, Julian McAuley and 1 more

Published Oct 6, 2026 · ▲ 3 on Hugging Face

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arXivAdversarial robustness

AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World Model

AdvSim2Real co-evolves tasks, adversarial injections, and a web agent in a simulator, boosting 4B agent completion by 33.6% against unseen adaptive attacks and transferring gains to real browsers.

Sarim Hashmi, Mukul Ranjan, Kshitij Mishra, Mikhail Kuznetsov and 2 more

Published Oct 6, 2026 · ▲ 3 on Hugging Face · Code

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arXivRL for LLMs

NeMo-DCR: Bit-Exact Delta-Compressed Refit for Scalable Agentic RL at Trillion-Parameter Scale

NeMo-DCR bit-exactly refits trillion-parameter policies by streaming delta-compressed weight changes via affine mappings and XOR masks, cutting 1T cross-region refits from 87.5 minutes to 150 seconds.

Songlin Jiang, Zhiyu Li, Terry Kong, Yu Yao and 4 more

Published Oct 6, 2026 · ▲ 6 on Hugging Face · Code ★ 2,048

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arXivRobot manipulation

EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation

EmbodiedSmith unifies asset, scene, and task generation in a recursive self-improvement loop to scale embodied simulation data, improving generation success and robot policy generalization across diverse embodiments and physics.

Yikai Qin, Yifei Deng, Mingjian Liang, Wenxuan Song and 12 more

Published Oct 6, 2026 · ▲ 7 on Hugging Face

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arXivRL for LLMs

HiPLEX: Hierarchical Policy Factorization for Full Duplex Speech Language Models

HiPLEX factorizes full-duplex speech policies into timing and content controllers to jointly optimize interaction dynamics via reinforcement learning. It lowers takeover rates, reduces interruption latency, and improves human-like turn timing versus GRPO.

Kyudan Jung, Hyunsin Park, Yoonhyung Lee, Jinhwan Park and 4 more

Published Oct 6, 2026

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arXivTool use & function calling

Hiding Tool Latency in On-Device Cascaded Voice Agent through Speculative Execution

Speculative tool execution predicts tool calls from partial ASR to run them during speech, cutting median voice-agent response latency from 5.79 s to 4.60 s.

Kyudan Jung, Hyunsin Park, Yoonhyung Lee, Jinhwan Park and 4 more

Published Oct 6, 2026 · ▲ 1 on Hugging Face

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arXivVideo generation

ALIVE: Interaction-Aligned Object Insertion for First-Frame-Guided Video Editing

ALIVE inserts objects that interact with video contents via first-frame editing and interaction guidance, outperforming baselines on interaction and insertion benchmarks.

Zhenghong Zhou, Zhe Lin, Jiebo Luo, Yuqian Zhou

Published Oct 6, 2026 · ▲ 3 on Hugging Face · Code

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arXivSoftware engineering agents

Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

Dev-Primitives turn repository artifacts into active, resident-LLM agents with self-modification interfaces, and HERMES improves software engineering benchmarks by 12.4% over baselines while cutting inference costs by 26.2%.

Haibo Jin, Xinjie Li, Peng Kuang, Haohan Wang

Published Oct 6, 2026 · ▲ 2 on Hugging Face

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arXivGANs & VAEs

Empirical Variational Autoencoder

Empirical Variational Autoencoder learns autoregressive latent priors empirically via one linear layer to close the VAE prior-posterior gap, yielding high-fidelity sequential generation competitive with diffusion models at much faster inference.

Kaede Shiohara

Published Oct 5, 2026 · ▲ 7 on Hugging Face · Code ★ 4

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arXivRobot manipulation

Execution-Aligned Progressive Noise for Consistent Asynchronous Replanning in Generative Robot Policies

Execution-Aligned Progressive Noise structures noise across chunks and time to maintain consistent generative states during asynchronous replanning, achieving up to 96.7% real-robot success.

Di Wu, Ping Liu, Xuhua Chen, He Zheng and 2 more

Published Oct 5, 2026

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arXivMixture of experts

Stepped MoE: Segment-Level Routing with Configurable Inference Complexity

Stepped MoE unifies elastic architectures and sparse gating to adapt model capacity to deployment constraints and input requirements, outperforming dense counterparts by 2-5%.

Arnav Kundu, Zhaoyang Xu, Bairu Hou, Chang Gao and 2 more

Published Oct 5, 2026 · ▲ 1 on Hugging Face

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arXivVision-language-action models

RealtimeWAM: One-Step Asynchronous World Action Models

RealtimeWAM uses teacher-anchored consistency distillation and cross-expert wavefront pipelining for one-step asynchronous action generation, achieving near-lossless performance with ~25x speedup.

Chengtao Lv, Jinyang Du, Shuyi Feng, Yang Yong and 6 more

Published Oct 5, 2026 · ▲ 12 on Hugging Face · Code ★ 2,880

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ICML 2026Alignment & preference optimization

HuatuoGPT-3: RL-Only Domain Adaptation from Base Models

OnePO enables RL-only medical domain adaptation via adaptive objective evolution and teacher retirement, yielding HuatuoGPT-3 that surpasses frontier models.

Junying Chen, Xinyuan Xie, Ziniu Li, Wenyuan Gu and 6 more

Published Oct 5, 2026 · ▲ 15 on Hugging Face · Code ★ 12

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NeurIPS 2026RL for LLMs

Rationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding

RGPO adaptively uses ground-truth rationales as temporary scaffolds to generate improved responses for on-policy RL, then transfers only higher-reward model outputs back, reducing reward sparsity and improving text and multimodal reasoning.

Hoang Phan, Minh Pham, Chau Pham, Chinmay Hegde and 2 more

Published Oct 5, 2026 · ▲ 7 on Hugging Face · Code ★ 1

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arXivImage recognition

WildMatch: Weakly Supervised Image Matcher Adaptation for Wildlife Re-Identification

WildMatch adapts pretrained image matchers to wildlife identification using only identity labels, improving retrieval accuracy and learning transferable matching priors without keypoint annotations.

Turhan Can Kargin, Piotr Kubaty, Ekaterina Rostovskaya, Izabela Wierzbowska and 2 more

Published Oct 5, 2026 · ▲ 2 on Hugging Face · Code

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arXivVideo generation

S2PD: Serial-to-Parallel Diffusion for Physically and Logically Consistent Video Generation

S2PD switches from autoregressive to parallel diffusion during denoising to enforce physical and logical consistency with faster sampling than fully serial methods.

Jeffrey Hu, Daniel Olmeda Reino, Ayush Tewari

Published Oct 5, 2026 · 0 citations · ▲ 1 on Hugging Face · Code ★ 4

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arXivDeep RL

MEND: RL For Flow Models via Proximal Velocity Matching

MEND uses proximal velocity matching to cap rewards and accept only cost-effective sample moves, outperforming prior flow-model RL methods in far fewer updates without KL penalties or reference models.

Shreshth Saini, Neil Birkbeck, Yilin Wang, Balu Adsumilli and 1 more

Published Oct 5, 2026 · ▲ 2 on Hugging Face · Code ★ 1

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arXivRobot manipulation

Conditional Trajectory Peaks: Single-Pass Multimodal Policies over Action Chunks

Conditional Trajectory Peaks predicts multimodal action-chunk candidates in a single pass, achieving 97.25% LIBERO success and 3× faster inference while preserving diverse behaviors.

Di Wu, Rongtian Shen, Ping Liu, Xuhua Chen and 3 more

Published Oct 5, 2026 · ▲ 1 on Hugging Face

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arXivProbing & representation analysis

Learning to Read the Contextual Tokens in Diffusion Transformers

A framework maps diffusion transformer contextual tokens through a frozen LLM to reveal they encode global emerging scene semantics early, inspiring contextual alignment that improves generation quality.

Omer Dahary, Etai Sella, Hadar Averbuch-Elor, Daniel Cohen-Or and 1 more

Published Oct 5, 2026 · ▲ 5 on Hugging Face

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arXivTool use & function calling

Judged Useless, Queried Anyway: Tool-Using Agents Rarely Turn Their Own Evidence Judgments into Stopping Decisions

Agents judge failing retrieval results useless but rarely stop; enforcing answers after five useless judgments improves success and fixes stopping.

Chubin Zhang, Zhenglin Wan, Xingrui Yu, Jingxuan Wu and 3 more

Published Oct 5, 2026 · ▲ 3 on Hugging Face · Code ★ 3

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arXivImage restoration

JLD: Perceptual Distance Through A Jacobian Lens

JLD defines a perceptual image distance via a Jacobian-derived metric tensor from frozen vision encoders, achieving state-of-the-art correlation with human judgments and resolution robustness.

Shreshth Saini, Balu Adsumilli, Alan C. Bovik

Published Oct 5, 2026 · ▲ 3 on Hugging Face · Code ★ 3

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arXivLong-context modeling

HLA: Expressive Hybrid Linear Attention via Chunk-Wise Dynamic Mixing

Hybrid Linear Attention introduces query-dependent chunk-level routing for Gated DeltaNet, improving long-context benchmarks by up to 5.57 points via adaptive recurrent memory composition.

Zhuokun Chen, Xi Lin, Xiyu Wu, Jiahao He and 2 more

Published Oct 5, 2026 · ▲ 2 on Hugging Face

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arXivAgent benchmarks & environments

MiniCorp: The Last Mile of the AI Agent Firm

MiniCorp is a simulated office environment that generates longitudinal, counterfactual enterprise data to study autonomous AI-run companies and train adaptive agents.

Jingying Zeng, Zhenwei Dai, Jinning Li, Changho Shin and 5 more

Published Oct 5, 2026 · ▲ 8 on Hugging Face

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arXivAlignment & preference optimization

Collaborative Personalized Preference Alignment for LLMs under Data Deficiency

APO learns shared LLM aligner initializations via grouped gradient coordination to enable few-shot personalization under heterogeneous preferences and scarce feedback, improving over baselines with 20 local examples.

Liyan Yang, Yige Yuan, Zhiqin Yang

Published Oct 5, 2026 · ▲ 5 on Hugging Face

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arXivRobot manipulation

InterMimicGen: Scaling Humanoid Loco-Manipulation through Self-Evolving Motion Imitation

InterMimicGen retargets human motion capture to humanoids and self-evolves tracking data via iterative simulation-verified augmentation to scale dexterous loco-manipulation.

Yucheng Zhang, Sirui Xu, Jinhong Li, Liuyu Bian and 7 more

Published Oct 5, 2026 · ▲ 4 on Hugging Face

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arXivVision-language-action models

Arm-wise Compositional Generalization in Dual-Arm Vision-Language-Action Models

ACG-Bench evaluates arm-wise compositional generalization in dual-arm vision-language-action models via AE-VLA, which achieves 21.53% simulated and 39% real-world success versus under 6% baselines.

Zaibin Zhang, Binghao Ran, Yuhan Wu, Zhongbo Zhang and 9 more

Published Oct 5, 2026 · ▲ 4 on Hugging Face

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arXivLLM agents & planning

Beyond Semantic Similarity: Performance and Costs of Agentic Retrieval for Complex Tasks

Agentic retrieval combining LLM reasoning with dense retrieval improves nDCG@10 by 8.7 points over standard retrieval but requires 107 seconds and 764K input tokens per query.

Reza Esfandiarpoor, Radek Osmulski, Yauhen Babakhin, Gabriel de Souza P. Moreira and 7 more

Published Oct 5, 2026 · ▲ 7 on Hugging Face

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arXivLLM reasoning & chain of thought

Sharpen Without Search: On-Policy Distillation of Sequence-Level Power Distribution

On-policy power distillation trains models to generate sharpened answers directly, improving single-sample math reasoning by up to 27.3 points and outperforming multi-candidate sampling and reward-based methods.

Erfan Baghaei Potraghloo, Seyedarmin Azizi, Arya Fayyazi, Saeid Shokoufa and 3 more

Published Oct 5, 2026 · ▲ 4 on Hugging Face · Code ★ 1

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arXivVision-language-action models

When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models

RACE predicts subskill transition timing to extend VLA action chunks reliably, reducing stop-and-go idle time ~5x on real robots while improving success rates.

Seonghoon Yu, Dongwon Kim, HyungRok Jung, Yoonjae Baek and 3 more

Published Oct 5, 2026 · ▲ 13 on Hugging Face · Code ★ 3

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arXivUncertainty & calibration

Certification of Real Images through Calibrated Content Authentication

Deepfake detectors degrade to 76% accuracy and near-zero under attacks, so calibrated reconstruction-based authentication bounds false real-image certification to 1%.

Sarim Hashmi, Abdelrahman Elsayed, Mohammed Talha Alam, Samuele Poppi and 1 more

Published Oct 5, 2026 · ▲ 13 on Hugging Face · Code ★ 2

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WWW 2026LLM reasoning & chain of thought

Base Models Can Reason By Taking a Cue From Training Data

Fixing initial token cues in base models boosts reasoning to match RL performance, with effects traced to training data associations that can be causally edited.

Sophie L. Wang, Amil Dravid, Rulin Shao, Kevin Farhat and 2 more

Published Oct 5, 2026 · ▲ 12 on Hugging Face · Code ★ 2

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arXivVideo generation

HLA-WM: Hybrid Linear Attention for Long-Horizon Video World Models

HLA-WM combines geometry-guided retrieval with recurrent linear attention to fix long-range forgetting in video world models, improving 60-second consistency metrics by up to 28.5% with 12× lower memory and no retraining.

Zhuokun Chen, Feng Chen, Xi Lin, Xiyu Wu and 3 more

Published Oct 5, 2026 · ▲ 6 on Hugging Face · Code ★ 2

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arXivRL for LLMs

LoGRA: Scaling LLM Reinforcement Learning with Low-Rank Gradient Sketches

LoGRA reduces LLM reinforcement learning memory by up to 45.7% via low-rank gradient sketches and predicted-KL step control, enabling 27B-parameter training on single nodes.

Shaokun Zhang, Yifan Zhang, Jian Hu, Yueying Li and 4 more

Published Oct 5, 2026 · ▲ 11 on Hugging Face

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arXivEfficient inference & serving

Closing the Context Gap: Activation Alignment for Tabular In-Context Learning

Activation alignment trains a linear map to align partial-context student activations with full-context teacher activations, significantly improving tabular in-context learning efficiency and recovering much of the performance gap.

Yoel Zeldes

Published Oct 5, 2026 · ▲ 5 on Hugging Face · Code ★ 1

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76%Highly rated
ICLR 2027Tabular data

Adapting prior-data fitted networks for tabular anomaly detection

Frozen and fine-tuned TabPFN representations for tabular anomaly detection yield ZEN and FOCUS, surpassing all ADBench baselines in AUROC despite unsupervised deployment and contaminated reference sets.

Maximilian Bershtman, Niv Cohen

Published Oct 5, 2026 · ▲ 5 on Hugging Face · Code ★ 1

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arXivIn-context learning & prompting

Learning to Learn a Language

Prior-Fitted Language Model, trained solely on synthetic non-linguistic data, learns to infer and predict real languages from context with frozen weights, achieving strong cross-lingual compression and reasoning without ever seeing real text.

Lennart Carstens-Behrens, Holger Fröhlich

Published Oct 5, 2026 · ▲ 7 on Hugging Face · Code ★ 1

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arXivAI oversight & deception

SoK: Semantic Decision Engines in Network Control Loops

Systematizing 139 semantic decision engine families reveals most miss network deadlines and verification, with only four reporting deadline attainment; unverified decisions reverse admission verdicts under queued execution, prompting minimum reporting rules and a research agenda.

Delong Li, Chen Li, Xu Wang, Haochen Gong and 2 more

Published Oct 5, 2026 · ▲ 6 on Hugging Face · Code

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arXivFairness & bias

Noise Out, Bias In: Targeted Bias Injection in Diffusion Language Models via Closed-Loop Activation Steering

Targeted bias injection via closed-loop activation steering exploits diffusion language model denoising trajectories to steer frozen models toward adversarial demographic answers with minimal corruption.

Sarim Hashmi, Mukul Ranjan, Abdelrahman Elsayed, Muhammad Umer Sheikh and 2 more

Published Oct 5, 2026 · ▲ 14 on Hugging Face · Code ★ 3

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arXivFairness & bias

FairRSFM: A Biome-Aware Benchmark and Debiasing Framework for Remote Sensing Foundation Models

FairRSFM benchmarks remote sensing foundation models by biome to expose hidden ecological performance disparities and tests debiasing methods without backbone updates. Aggregate metrics consistently mask large biome-dependent gaps, though mitigation effectiveness varies by model and task.

Md Aminur Hossain, Omkumar Vaghasiya, Rajeev Ranjan Dwivedi, Vinod Kurmi and 1 more

Published Oct 5, 2026 · ▲ 5 on Hugging Face · Code

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arXivLLM reasoning & chain of thought

What Matters for Latent Reasoning with Flow Matching

FLaRe uses flow matching for latent reasoning that is useful, diverse, explainable, refinable and efficient, reaching 97% of explicit chain-of-thought accuracy at 25% latency.

Yassine Ouali, Adrian Bulat, Georgios Tzimiropoulos

Published Oct 5, 2026 · ▲ 10 on Hugging Face

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arXivAgent memory

Capability-Driven Self-Evolution of Agent Memory

PrisMem drives agent memory self-evolution via capability-specific guidance, dependency-aware selection, and trace-guided integration, outperforming baselines by up to 10.54 points on million-token benchmarks.

Yaoqi Chen, Yuru Feng, Qianxi Zhang, Baotong Lu and 7 more

Published Oct 5, 2026 · ▲ 6 on Hugging Face

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arXivAlignment & preference optimization

Representation-Space MMD for Diffusion Language Models

Post-training minimizes representation-space MMD between diffusion language model outputs and references via retained token features, improving perplexity, accuracy, and parallel decoding.

Ilya Drobyshevskiy, Ilia Sudakov, Maksim Semenov, Denis Kuznedelev and 6 more

Published Oct 5, 2026 · ▲ 16 on Hugging Face · Code ★ 10

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arXivLLM pretraining & scaling laws

Towards Looped Models Done Right, Part II: Rethinking at Fixed Points

Looped language models use fixed-point convergence to enable truncated training, shared KV caches, faster prefill, and faster RL updates, while a learned depth prior and orthogonal input injection improve perplexity across scales.

Benhao Huang, Chufan Shi, Junlin Chen, Shicheng Wen and 3 more

Published Oct 5, 2026 · ▲ 17 on Hugging Face · Code ★ 30

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arXivAgent benchmarks & environments

AutoSciBench: Autonomous Benchmark Generation for Evaluating Scientific Agents

AutoSciBench autonomously generates and iteratively adapts scientific agent benchmarks via recipes and concepts, reducing solver accuracy by over 22 points versus human benchmarks while improving quality ratings.

Dongki Kim, Namkyeong Lee, Surag Nair, Carl Edwards and 6 more

Published Oct 4, 2026 · ▲ 17 on Hugging Face

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arXivLLM agents & planning

EVISKILL: Grounding Skill Evolution in Replayable Evidence

EVISKILL grounds LLM skill evolution in replayable evidence cards linking edits to supporting contexts, using targeted replay for verification and global validation for incorporation.

Yan Zhou, Yili Wang, Yiwei Dai, Qinggang Zhang and 1 more

Published Oct 4, 2026 · ▲ 11 on Hugging Face · Code ★ 8

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arXivVision-language-action models

A Safe Action Is Not Enough: Feasible-Future Decoding for Vision-Language-Action Policies

Feasible-future decoding reranks VLA actions by future safe-completion mass, reducing cumulative safety costs by up to 57.5% without retraining or rollouts.

Tu Nguyen, Matthieu Zimmer, Vu Anh Vu, Ziyi Wang and 3 more

Published Oct 4, 2026 · ▲ 3 on Hugging Face

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arXivDiffusion models

LiFT: Loop Flow Transformers

Loop Flow Transformers loop a shared diffusion transformer with depth-indexed regression targets, improving generation with more inference compute and fewer parameters than dense models.

Mohammad Mahdi Derakhshani, Pedro M. P. Curvo, Gertjan J. Burghouts, Jan-Willem van de Meent and 1 more

Published Oct 4, 2026 · ▲ 9 on Hugging Face

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arXivAgent benchmarks & environments

UndoBench: Separating Task Competence from Recovery Capability in Tool-Using AI Agents

UndoBench separates tool-using agent competence from fault recovery via paired enterprise workflow trials, finding 83.54% nominal success but only 46.72% recovery success with phase-dependent vulnerabilities.

Dolly Sah, Tanmay Sah, Harshul Jain, Tanya Sah

Published Oct 4, 2026 · ▲ 11 on Hugging Face · Code ★ 1

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arXivRobot manipulation

RobotUse: Allocating Computation, Context, and Decisions

RobotUse organizes robot computation, context, and decisions around revisable physical actions via visual target selection and persistent playbooks, achieving 45% RoboLab success and real-world learning.

Junhoo Lee, Injun Baek, Seungyeon Kim, Suhyun Jeon and 3 more

Published Oct 4, 2026 · ▲ 14 on Hugging Face · Code ★ 4

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arXivLLM agents & planning

ASCENT: Online Test-Time Training of Long-Horizon Agents via Self-Distillation of Verified Experience

ASCENT online test-time trains agents by self-distilling verified deployment trajectories into LoRA weights via a frozen hindsight model, improving long-horizon success and efficiency without external teachers or memory retrieval.

Haodong Lu, Dong Gong

Published Oct 4, 2026 · ▲ 17 on Hugging Face

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arXivLLM agents & planning

Code2Games: Enabling Coding Agents for Gaming World Generation

Code2Games coordinates scene analysis and gameplay planning via shared representations to generate consistent gaming worlds and adapt them to Unreal Engine 5. The framework improves visual quality, interactive fidelity, and playable-game quality over direct coding-agent generation on the GameCode4D

Wei Wu, Ziyang Xu, Zeyu Zhang, Yang Zhao and 1 more

Published Oct 4, 2026 · ▲ 6 on Hugging Face · Code ★ 4

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arXivVision-language-action models

DiVeR: Decision-Critical Verifier Learning for VLA Test-Time Scaling

DiVeR improves verifier-guided VLA test-time scaling by reweighting learning toward decision-critical states using action representation dispersion, boosting success without extra annotations or overhead.

Seongheon Park, Heecheol Kim, Shulin Tian, Lilika Makabe and 4 more

Published Oct 4, 2026 · ▲ 1 on Hugging Face

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arXivLLM agents & planning

SearchJev: A Fast and Calibrated System-1 Model for Search Agents

SearchJev is a fast calibrated System-1 model that scores search decisions directly without autoregressive generation, improving decision quality, speed, and calibration over same-size language models.

Congfeng Cao, Lipeng Zuo, Konstantinos Papakostas, Qiwei Xu and 5 more

Published Oct 4, 2026 · ▲ 14 on Hugging Face · Code ★ 4

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arXivTest-time compute

Self-Generated Feedback Destabilizes Test-Time Training: A Causal Decomposition of Long-Horizon Adaptation

Self-generated feedback in long-horizon test-time training causes weight updates that improve synthetic text but degrade real-text prediction, and settlement on independent evidence prevents this failure.

Cheng Luo, Bing Li, Bernard Ghanem

Published Oct 4, 2026 · ▲ 19 on Hugging Face · Code ★ 1

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arXivAgent memory

Memadapter: Counterfactual Adaptation Against Memory-induced Sycophancy

MemAdapter counters memory-induced sycophancy via counterfactual induction, context-aware reflection, and evidence-based reasoning to improve memory reliability across diverse scenarios.

Ruqing Ning, Haibo Meng, Zhishang Xiang, Zerui Chen and 3 more

Published Oct 4, 2026 · ▲ 27 on Hugging Face · Code ★ 21

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arXivUnified multimodal models

Prism: Dynamic Sparse Attention for Native 2K Joint Video-Audio Generation Model Training

Prism introduces dynamic sparse attention via adaptive macro-zone block shapes guided by visual variance and cross-modal attention for 2K joint video-audio generation, yielding 2.5x training speedup and improved quality.

Shuyuan Tu, Qi Tian, Yinming Huang, Yue Wu and 7 more

Published Oct 4, 2026 · ▲ 4 on Hugging Face · Code ★ 30

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arXivUnified multimodal models

Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation

Kandinsky 6.0 Video introduces diffusion models that generate synchronized 5-second audio-video clips with lip-sync via a dual-stream CrossDiT architecture, with the 29B-parameter Pro version outperforming its predecessor and matching top competitors in speech quality.

Team Kandinsky, Julia Agafonova, Bulat Akhmatov, Mikhail Aksyutin and 36 more

Published Oct 4, 2026 · ▲ 113 on Hugging Face · Code ★ 119

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PreprintU EdinburghProteins

Large-scale analysis of AlphaFold structures reveals organism-specific physicochemical signatures

Large-scale AlphaFold structure analysis reveals organism-specific physicochemical signatures reconstructed via DE-STRESS metrics across 48 proteomes and PDB structures.

Michael J. Stam

Published Oct 4, 2026 · 0 citations

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NeurIPS 2026Video-language models

Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End Latency

LoHi trades per-frame resolution for denser temporal sampling via low-resolution streams plus sparse high-resolution frames, boosting long-video accuracy up to 10.6 points and cutting front-end latency up to 7x.

Sixun Dong, Wei Li, Andong Deng, Qi Qian and 3 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published Oct 3, 2026 · ▲ 13 on Hugging Face

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ICML 2026Explainable AI

ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution

ConEx bridges saliency maps with concept reasoning via automatic concept discovery to generate faithful, human-interpretable visual explanations.

Yehonatan Elisha, Oren Barkan, Ziv Weiss Haddad, Noam Koenigstein

Published Oct 3, 2026 · 0 citations · ▲ 1 on Hugging Face

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arXivAlignment & preference optimization

DiffGate: Difficulty-Gated Teacher Guidance for On-Policy Distillation

DiffGate gates on-policy teacher guidance by trajectory failure and group difficulty to combine dense token-level updates with outcome-level GRPO rewards, improving student pass rates.

Karn Tiwari, Varnith Chordia, Prathosh A P

Published Oct 3, 2026 · ▲ 9 on Hugging Face

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arXivGANs & VAEs

Learning Discriminative Geometry for Drifting Models

Drifting models suffer from poor pixel-space performance because representation geometry controls KDE sample weighting; persistent representation learning learns discriminative geometry from raw pixels, cutting FID by 82, 95% without pretrained encoders.

Doudou Zhang, Wenwen Hou, Yilin Chen, Qi Chen

Published Oct 3, 2026 · ▲ 4 on Hugging Face · Code ★ 3

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arXiv3D generation

DistScene: Object-to-Scene Distillation for 3D Scene Generation

DistScene generates compositional 3D scenes from single images via object-to-scene distillation, improving spatial coherence by modeling environments as explicit components with shared coordinate frames.

Kunming Luo, Hongyu Yan, Ken Deng, Chengcheng Zhou and 5 more

Published Oct 3, 2026 · ▲ 4 on Hugging Face

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arXivVision-language-action models

PerturBot: Breaking Shortcut Priors in Vision-Language-Action Models with Perturbative Training

PerturbBot breaks vision-language-action shortcut priors via perturbative training while GroundingFscore diagnoses shortcut reliance, enabling healthier scaling without altering inference.

Mingyu Liu, Chonghao Sima, Tianjian Feng, Hanqing Wang and 3 more

Published Oct 3, 2026 · ▲ 13 on Hugging Face · Code ★ 6

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NeurIPS 2026Meta, transfer & few-shot learning

PaLoRA: Paced Low-Rank Adaptation for Continual Learning

PaLoRA derives an optimal rank-aware pacing law for LoRA continual learning that adaptively restricts gradient scaling to prevent forgetting, improving long-horizon benchmark accuracy by 4%.

Yuxuan Li, Fanhu Zeng, Hao Tang

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published Oct 3, 2026 · ▲ 9 on Hugging Face · Code ★ 2

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arXivMedical LLMs

Agentic discovery of blood biomarker from distilled private health records

Distilling private health records into a released scoring tool enables agentic discovery of CBC biomarkers that improve diagnostic AUC over literature baselines without exposing patient data.

Seffi Cohen, Liat Antwarg Friedman, Amir Anisman, Ruth Johnson and 6 more

Published Oct 3, 2026 · ▲ 4 on Hugging Face · Code

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arXivQuantization

CurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model

CurveCodec 2 predicts quantized skeletal curves from past values and learns residual entropy models to reduce animation storage to 0.22-0.37x of ACL with verified error bounds.

Mingyi Shi, Huancheng Lin, Xuelin Chen, Taku Komura

Published Oct 3, 2026 · ▲ 4 on Hugging Face · Code ★ 5

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arXivMachine unlearning

UnAct: Gradient-Free Unlearning via Targeted Activation Intervention

UnAct uses gradient-free targeted activation interventions to unlearn model classes from few forget images without gradients, labels, or retained data, matching or exceeding SSD and LFSSD accuracy across datasets and preventing network collapse with scarce data.

Saeed Abdul Muizz, Aayat Rafiq, Iqra Altaf Gillani, Janibul Bashir

Published Oct 3, 2026 · ▲ 4 on Hugging Face · Code ★ 1

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arXivLLM pretraining & scaling laws

The Numerical Linear Algebra of Large Language Models

This survey explains large language model core concepts to numerical analysts and highlights key numerical linear algebra contributions to LLM techniques.

Abdelkader Baggag, Yousef Saad

Published Oct 3, 2026 · ▲ 4 on Hugging Face

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arXivAgent benchmarks & environments

LMBuild: Evaluating LLM Agents for Generating Buildable and Functional Structures

LMBuild evaluates LLM agents on generating buildable, functional 3D structures and finds physical operability and functional affordance remain challenging despite improved soundness.

Jiateng Liu, Rushi Wang, Cheng Qian, Xuejun Zhang and 8 more

Published Oct 3, 2026 · ▲ 24 on Hugging Face · Code ★ 1

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arXivTest-time compute

ALoDLM: Adaptively Looped Diffusion Language Models

ALoDLM applies token-adaptive latent recurrence to diffusion language models, allocating computation by difficulty to close the quality gap with autoregressive models at 1.7B and 8B scales.

Liancheng Fang, Zhuowei Li, Youngeun Kim, Tianchen Zhao and 9 more

Published Oct 3, 2026 · ▲ 55 on Hugging Face · Code ★ 4

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arXivLong-context modeling

Periscope: Extending Frozen Language Models Beyond Their Context Window

Periscope arranges text chunks in a grid to build an evidence map via local and strided probes, letting frozen language models answer questions across multi-million-token contexts with sublinear cost and small GPU memory.

Mohamed Eltahir, Anas Obayd, Raed Rashid, Abdulrahman Alghamdi and 4 more

Published Oct 2, 2026 · ▲ 8 on Hugging Face · Code ★ 1

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arXivRobot manipulation

World Action Learning via Interaction-Centric Spectral Latent Guidance

WING distills interaction-centric latent actions from egocentric video and uses cross-embodiment spectral low-frequency guidance to transfer them to robot policies, achieving high success rates on LIBERO, RoboTwin, RoboCasa, and real-world tasks.

Zhiming Liu, Yikun Miao, Ying Chen, Hongrui Yin and 6 more

Published Oct 2, 2026 · 0 citations · ▲ 20 on Hugging Face

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arXivRL for LLMs

OPD Before RL: Warm-Starting Rubric-Based RL with On-Policy Distillation

Rubric-privileged on-policy distillation before reinforcement learning improves open-ended task scores and reduces reward hacking versus supervised fine-tuning baselines.

Xinpeng Wang, Wei Shi, Yu-Chia Chen, Maria Zontak and 2 more

Published Oct 2, 2026 · 0 citations · ▲ 3 on Hugging Face

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arXivVideo generation

DuoMatching: Joint-Marginal Distribution Matching for Few-Step Video Generation

DuoMatching improves few-step video generation by jointly matching frame distributions and adding frame-level supervision via an image teacher, boosting visual quality and semantic alignment over 80%.

Jiahao Zhan, Yan Wang, Yongrui Ma, Qunliang Xing and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 17 on Hugging Face · Code ★ 4

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arXivLLM pretraining & scaling laws

Do Language Models Need a Trainable Input Embedding Table? Fixed Minimal Token Codes at 1.7B-Class Scale

Fixed token codes can replace trainable input embeddings in 1.7B-scale language models, removing 100.7M parameters while preserving substantial capabilities without requiring token-specific vectors.

A. Bochkov

Published Oct 2, 2026

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arXivRobot manipulation

EyeRobot 2.0: Active Gaze for Precise Manipulation without Wrist Cameras

EyeRobot 2.0 uses active gaze and fixation-relative frames to enable precise bimanual manipulation with only a single stereo camera, outperforming passive stereo by 40% in real-world trials and doubling ego-plus-wrist success under occlusion.

Kush Hari, Justin H. Kerr, Nidhya Shivakumar, Samarth Mahapatra and 6 more

Published Oct 2, 2026 · 0 citations · ▲ 10 on Hugging Face

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arXivSim-to-real

Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation

Skill2Real learns simulation skills via a shared robot API with a Proposer-Verifier-Governor loop, transferring frozen skill hierarchies to real robots without fine-tuning to reach 78.75% real-world manipulation success.

Xincheng He, Siyu Ma, Chang Yu, Yunuo Chen and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 16 on Hugging Face

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arXivLLM reasoning & chain of thought

Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability

Efficient reasoning training differs in impact: faithfulness usually drops due to inconsistency, but monitorability remains robust.

Samuel Lewis-Lim, Xingwei Tan, Mario Sänger, Zhixue Zhao and 1 more

Published Oct 2, 2026 · 0 citations · ▲ 13 on Hugging Face

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arXivFairness & bias

Collective Bias Mitigation via Model Routing and Collaboration

Collective Bias Mitigation routes queries among diverse LLMs and fosters collaboration to substantially reduce bias over single-model baselines.

Mingzhe Du, Luu Anh Tuan, Xiaobao Wu, Yichong Huang and 6 more

Published Oct 2, 2026 · 0 citations · ▲ 14 on Hugging Face

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arXivLLM evaluation & benchmarks

Multilingual GSM-Symbolic: What determines capability transfer across languages?

Multilingual GSM-Symbolic introduces matched math problems across 15 languages to show model size, resource level, reasoning, and typology determine cross-lingual transfer, with size and reasoning closing low-resource gaps but not typological ones.

Kenneth Enevoldsen, Riley Herchert, Sofie Mosegaard, Dan Saattrup Smart and 21 more

Published Oct 2, 2026 · 0 citations · ▲ 47 on Hugging Face · Code ★ 4

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arXivAutoregressive generation

ProAR: Learning Prospective Reasoning with Autoregressive Video Models

ProAR introduces goal-frame prediction and future self-alignment to enable goal-directed reasoning in autoregressive video models, surpassing baselines with 25% training steps.

Linghui Shen, Tinghui Zhu, Sheng Zhang, Muhao Chen

Published Oct 2, 2026 · 0 citations · ▲ 26 on Hugging Face · Code ★ 2

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arXivLLM agents & planning

Source Preference in the Wild: How LLM Agents Favor Items by Source, and How to Reduce It

LLM agents show strong source preferences across search domains that can override item quality, though supplying missing information or countering preconceptions reduces this bias.

Jonghyun Song, Haewon Park, Jeonghoon Shim, Woojung Song and 1 more

Published Oct 2, 2026 · 0 citations · ▲ 37 on Hugging Face

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arXivRobot manipulation

PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation

PointWAM forecasts 3D point trajectories of scenes and hands in a shared space-time frame to guide dexterous robot manipulation, improving DexJoCo success by 56.9 points with video pre-training.

Chunghyun Park, Beomjun Kim, Seungcheol Park, 권희승 and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 42 on Hugging Face

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arXivLLM agents & planning

Scaling Trajectories for Complex Tasks through Recursive Self-Rewrite

Recursive Self-Rewrite uses diverse harnesses and recursive revision to rewrite successful terminal trajectories for supervised fine-tuning, boosting pass@3 by up to 7.6x on hard benchmarks.

Zongxia Li, Yucheng Shi, Zhongzhi Li, Junyao Yang and 6 more

Published Oct 2, 2026 · 0 citations · ▲ 91 on Hugging Face

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arXiv3D vision & reconstruction

4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes

4DCodeBench benchmarks agents reconstructing dynamic scenes from video as executable graphics code, finding strong static models fail at complex dynamics.

Ruihong Shen, Žiga Kovačič, Peter Kulits, Xingrui Wang and 5 more

Published Oct 2, 2026 · 0 citations · ▲ 28 on Hugging Face · Code ★ 89

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arXivRL for LLMs

MetaRubric: Learning to Reward for Rubric-Based Reinforcement Learning

MetaRubric fixes vacuous rubric credit via evidence-aware optimization and counterfactual rubric adaptation, improving PubMedQA accuracy by up to 20.40 points over static-judge GRPO.

Yuxuan Fan, Jaehong Yoon

Published Oct 2, 2026 · 0 citations · ▲ 22 on Hugging Face · Code ★ 2

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arXivAlignment & preference optimization

Pivot-SD: Efficient Self-Distillation for Masked Diffusion Language Models

Pivot-SD self-distills masked diffusion language models by supervising high-impact commitment tokens via information-gain selection, improving reasoning with minimal data.

Seo Hyun Kim, Sunwoo Hong, Younwoo Choi, Chen-Hao Chao and 2 more

Published Oct 2, 2026 · 0 citations · ▲ 54 on Hugging Face

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arXivVideo-language models

World Embedding Benchmark

World Embedding Benchmark evaluates physical encoding via 8,000 simulation cases, finding alignment trades off against quantitative recoverability and retrieval improves video generation fidelity.

Yiqi Liu, Ruifeng Yuan, Yang Wang, Long Li and 6 more

Published Oct 2, 2026 · 0 citations · ▲ 44 on Hugging Face · Code ★ 4

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arXivCode generation

FrugalEvo: Towards Cost-Aware LLM-Guided Program Evolution

FrugalEvo pairs expensive LLM strategy exploration with cheap LLM implementation and caching to maximize optimization gain per cost under a budget, outperforming baselines on 10 tasks at significantly lower expense.

Hui Chen, Xuan Qi, James Zhao, Zhaopeng Feng and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 22 on Hugging Face · Code ★ 5

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arXivVideo generation

In-Distribution Forcing for Long Video Generation at Test Time

In-Distribution Forcing prevents out-of-distribution key-value drift via self-caching to extend short video models to minute-scale generation.

Jeongwoo Shin, Youngyoon Choi, Sangwoo Jo, Hyunmog Kim and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 29 on Hugging Face · Code ★ 3

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arXivLLM reasoning & chain of thought

Language Models that Play Chess and Explain Their Moves

Queen, a 4B-parameter chess-language model, plays at grandmaster level and explains moves via cross-attention to a silent expert encoder and iterative Bellman-style explanation distillation, surpassing larger frontier models.

Adithya Bhaskar, Jeffrey Cheng, Danqi Chen

Published Oct 2, 2026 · 0 citations · ▲ 31 on Hugging Face · Code ★ 18

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arXivVision-language-action models

Native Action-Prior Learning from Videos for World Action Models

NAVA-WAM pretrains robot action policies directly from observation-only videos via flow-matching and joint attention, improving control accuracy and label efficiency.

Zhaochong An, Fei Zhang, Menglin Jia, Duncan Frost and 9 more

Published Oct 2, 2026 · 0 citations · ▲ 81 on Hugging Face

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arXivLLM agents & planning

Harness-Aware Distillation for Small Language Model Agents

Harness-Aware Distillation focuses agent distillation on capabilities beyond the fixed harness via action preferences and validity checks, improving long-horizon agent performance without task rewards.

Moonseok Choi, Taehong Moon, Giung Nam, Juho Lee

Published Oct 2, 2026 · 0 citations · ▲ 4 on Hugging Face · Code

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arXivAgent benchmarks & environments

HyperBrowseComp: A Multilingual and Multimodal Stress Test for Web-Browsing Agents

HyperBrowseComp introduces a multilingual, multimodal web-browsing benchmark of 423 hard questions requiring obscure evidence discovery, and current agents perform poorly against human baselines.

Alham Fikri Aji, Faiz Rizki Ramadhan, Zayd M. K. Zuhri, Seung Hun Eddie Han and 13 more

Published Oct 2, 2026 · ▲ 53 on Hugging Face

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arXivLLM agents & planning

Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

ADSD links numerical diagnosis to reusable solver self-improvement, reducing mean solver error by nearly 71x across four challenging numerical domains.

Peter Chen, Wotao Yin

Published Oct 2, 2026 · ▲ 8 on Hugging Face

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arXivTime series forecasting

SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

SEER uses self-evolving event reasoning and retrieval to dynamically optimize forecasting with exogenous events via reflective memory and causal knowledge, outperforming state-of-the-art baselines.

Mingtian Tan, Palash Goyal, Mihir Parmar, Sarkar Snigdha Sarathi Das and 5 more

Published Oct 2, 2026 · ▲ 13 on Hugging Face · Code

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arXivPrivacy

What Gradients Add to Text Leakage in Split Language Models, Counted per Token and per Document

Split-language-model gradients boost token recovery to 97.38% and document reconstruction to 37.77%, so split traffic requires per-token and per-document leakage reporting.

Georgios Politis, Evangelos Pappas

Published Oct 2, 2026 · ▲ 8 on Hugging Face

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arXivMulti-agent LLM systems

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

SHIFT predicts harness utility via a local LLM to search multi-agent structures per query, achieving ~80% mean accuracy across benchmarks while reducing execution tokens by 32%.

Som Sagar, Shasha Li, Hejie Cui, Ransalu Senanayake and 1 more

Published Oct 2, 2026 · ▲ 10 on Hugging Face

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arXivProteins

Learning Latent Protein Languages for Autoregressive Generation

Learned latent protein languages improve autoregressive generation scaling, speed, and quality versus amino-acid and coordinate token models.

Mahdi Pourmirzaei, Farzaneh Esmaili, Amir Ziashahabi, Mohammadreza Pourmirzaei and 1 more

Published Oct 2, 2026 · ▲ 5 on Hugging Face · Code

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arXivVision-language models

DEPICT: Scoring Text-to-Image Alignment by Answer Agreement

DEPICT scores text-to-image alignment via expected agreement between image and caption answers, boosting negation accuracy to 88% and exceeding fine-tuned evaluators on human correlation benchmarks.

Vasco Ramos, Sandra Godinho Silva, Joao Magalhaes, Ricardo Rei and 1 more

Published Oct 2, 2026 · 0 citations · ▲ 3 on Hugging Face

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arXivVision-language models

Foresight: planning future perception in streaming VLMs without retraining

FORESIGHT uses dual-stream anticipatory planning in frozen streaming VLMs to dynamically configure future perception, improving online benchmarks by up to 18.7 points without retraining.

Ashok Prasad Neupane, Dipan Bartaula, Ankit Belbase, Saugat Adhikari and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 3 on Hugging Face · Code

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arXivAgent benchmarks & environments

Self-Supervised Scaling of Terminal Environments for Scientific Domains

Software-in-the-loop reconstruction scales terminal-agent training by deriving verified tasks from existing scientific workflows without manual references, improving Terminal-Bench 2 performance to 53.56%.

Zhongzhi Li, Yucheng Shi, Zongxia Li, Junyao Yang and 7 more

Published Oct 2, 2026 · 0 citations · ▲ 10 on Hugging Face

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arXivMultimodal hallucination

OmniConfess: Eliciting Token Confessions to Mitigate Omni-Modal Hallucination

OmniConfess mitigates omni-modal hallucinations by producing token-level confessions of evidential dependence to correct unsupported commitments across text, image, audio, and video.

Huiqiang Rong, Haoran Luo, Hui Feng, Zhonghong Ou and 3 more

Published Oct 2, 2026 · 0 citations · ▲ 6 on Hugging Face · Code ★ 1

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arXivDiffusion models

COSMI: COmpositional Synthesis of Multi-object Interactions

COSMI synthesizes multi-object interactions by composing local single-object clips, yielding a 222k-sequence dataset and a diffusion model that generalizes to unseen object-interaction pairs with higher contact accuracy.

Daniel Eskandar, Ilya A. Petrov, Gerard Pons‐Moll

Published Oct 2, 2026 · 0 citations · ▲ 7 on Hugging Face · Code ★ 8

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arXivDiffusion models

DMAD: Distribution Matching as Adversarial Distillation for Fast Visual Generation

DMAD recasts distribution matching as adversarial distillation with discriminator heads to eliminate auxiliary score models, achieving state-of-the-art few-step image, video, and audio-video generation.

Zhengming Yu, 袁俊坤, Haotian Yang, Gordon Guocheng Qian and 7 more

Published Oct 1, 2026 · 0 citations · ▲ 3 on Hugging Face · Code

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NeurIPS 2026Distribution shift & OOD detection

Optimal Transport Reweighting for Robust Learning under Spurious Correlations and Label Noise

POTER uses optimal transport geometry between training and reference distributions to downweight mislabeled or shortcut-aligned samples, achieving state-of-the-art worst-group accuracy with a single training stage.

Sung Ho Jo, Seonghwi Kim, Wonsang Yun, Minwoo Chae

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published Oct 1, 2026 · 0 citations

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arXiv3D generation

EditHero: A Benchmark for Long-Horizon Part-Level 3D Editing and Vibe Modeling

EditHero benchmarks long-horizon part-level 3D editing via sequential instructions and target images, finding agentic code-based methods preserve unedited regions better but are slower than non-agentic regeneration.

Ruihan Yu, Yu-Ju Tsai, Muyao Niu, Runyi Li and 8 more

Published Oct 1, 2026 · 0 citations · ▲ 50 on Hugging Face · Code ★ 12

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arXivVision-language-action models

Kinematic MeanFlow: One-Step Action Generation Policy for Robotic Foundation Models

Kinematic MeanFlow decouples MeanFlow's time derivative via a kinematic identity to stabilize one-step robotic action generation, cutting latency by up to 74% while outperforming multi-step flow matching.

Jiawei Fan, Sifeng Wang, Yuqing Hou, Anbang Yao

Published Oct 1, 2026 · 0 citations · Code

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arXivU California, Los AngelesMila - Quebec Artificial IntelliMcGillLLM pretraining & scaling laws

Cross-Lingual Alignment for Decoder-Only Models using MoE Routers

Cross-lingual MoE router alignment improves multilingual LLM performance by aligning router outputs across languages instead of hidden states.

Lucas Bandarkar, Clark Peng, Ahmed Haj Ahmed, Aditi Khandelwal and 1 more

Published Oct 1, 2026 · 0 citations · ▲ 1 on Hugging Face · Code

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arXivLLM reasoning & chain of thought

Hierarchical Continuous Diffusion Language Models

HC-DLM couples discrete token generation with a continuous latent trajectory via a unified variational denoising objective, outperforming diffusion baselines on Sudoku, Countdown, and language modeling.

Hui Ren, Zihan Li, Chang Liu, Huidong Liu and 1 more

Published Oct 1, 2026 · 0 citations · ▲ 89 on Hugging Face · Code ★ 57

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arXivWeb & GUI agents

AutoGUIWorld: Image Generators as Visual World Models for GUI Agent

AutoGUIWorld uses image generators to synthesize GUI interaction trajectories without running software, improving OSWorld scores to 40.8% and ScienceBoard success to 32.2%.

Cheng Yang, Yifan Wu, Yutao Huang, Zhaohua Zhang and 17 more

Published Oct 1, 2026 · 0 citations · ▲ 61 on Hugging Face · Code ★ 9

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arXivU Wisconsin–MadisonNew YorkStanfordRL for LLMs

Sharpening Tax in Post-Training

Post-training sharpens base model behaviors at the cost of solution coverage, introducing a quantifiable "Sharpening Tax"; a posterior-tempered group sampler reduces this tax while boosting accuracy.

Changdae Oh, Qi Zeng, Qi Qi, Andrey Zhmoginov and 6 more

Published Oct 1, 2026 · 0 citations · ▲ 102 on Hugging Face · Code ★ 25

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arXivLLM pretraining & scaling laws

Scaling and Distilling Text Embeddings for Better Diffusibility

Scaling and distilling text embeddings improves latent diffusion by yielding more connected, diffusible spaces that boost generative performance beyond autoregressive baselines.

Zekai Zhang, Yunjie Tian, Yanjin He, Xiaoyan Zhang and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 57 on Hugging Face · Code ★ 3

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arXivVideo generation

ROWBench: Do Video Models Render What the Program Specifies?

PROWBench evaluates video models' fidelity to program-specified world events via replayable world records and VLM-based logic-render and interaction metrics.

Zheng-Hui Huang, Guixu Lin, Yu-Ju Tsai, Jian-Kai Zhu and 5 more

Published Oct 1, 2026 · 0 citations · ▲ 70 on Hugging Face · Code ★ 31

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arXivAgent memory

Beyond Memory: Harnessing Long-Horizon Agents with Explicit Belief States

PoS maintains explicit belief states for long-horizon LLM agents, detects belief trapping, and recovers to achieve top results across four benchmarks.

Yu Luo, Jiamin Jiang, Yimin Zuo, Xidao Wen and 8 more

Published Oct 1, 2026 · 0 citations · ▲ 93 on Hugging Face · Code ★ 28

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arXivRobot manipulation

InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation

InterEvolve evolves reward programs at test time via an LLM agent and numerical optimizer to compose a humanoid controller's skills for novel loco-manipulation tasks. The approach releases latent controller competence through object-aware forward-backward models, generating novel strategies that tra

Zhuo Lin, Sirui Xu, Liuyu Bian, Yu-Xiong Wang and 1 more

Published Oct 1, 2026 · 0 citations · ▲ 61 on Hugging Face

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arXivVideo generation

World Observer: Joint Actor-Observer Generation for Persistent World Modeling

World Observer jointly generates actor and panoramic observer views to continuously model out-of-view dynamics via shared geometric warping and observer sinks.

Hyunwook Choi, Dahyun Chung, Hyunsung Kim, Siyoon Jin and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 85 on Hugging Face · Code ★ 30

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arXivInformation extraction

From Retrieval to Typed Decisions: Calibrated System One Models from Biomedical Sentence Encoders

Biomedical retrieval encoders adapt to typed decision models via SBERT2S1, with retrieval pretraining helping residual heads but not cross-heads, and cross-entropy outperforming RLCD by 2.5, 3.0 points after fixing biased reward normalization.

Pritam Deka

Published Oct 1, 2026 · 0 citations · ▲ 11 on Hugging Face · Code

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arXivUnified multimodal models

Octrees as an Explicit 3D Language

OctLLM represents 3D geometry via sparse octree tokens and trains separate 3D branches to achieve state-of-the-art multimodal 3D generation and understanding without degrading language ability.

Ran Dan, Si‐Tong Wei, Pengfei Xiong, Wei Zhang and 2 more

Published Oct 1, 2026 · 0 citations · ▲ 11 on Hugging Face · Code ★ 12

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arXivMultimodal reasoning

CANOPY: Adaptive-Granularity Evidence Compression for Multimodal RAG

CANOPY adaptively compresses multimodal evidence via hierarchical region scoring and targeted retrieval, improving QA accuracy while reducing input tokens by up to 27.7%.

Hyojeong Yun, Jueun Kim, Wook-Shin Han

Published Oct 1, 2026 · 0 citations · ▲ 16 on Hugging Face

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arXivRL for LLMs

From Gradients to Capabilities: Understanding Multi-Teacher On-Policy Distillation

Multi-teacher on-policy distillation integrates RL teacher gradients via loss averaging, Adam smoothing, and BF16 rounding, with averaging rules significantly altering math accuracy outcomes.

Siqi Zhu, Suozhi Huang, Kaixuan Zhang, Yuheng Yang and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 13 on Hugging Face

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arXivLLM pretraining & scaling laws

Looping Beyond Twice: A Scalable Recipe for Looped Mixture-of-Experts

LOOM stabilizes looped MoE via bounded residual updates and per-loop routers to scale loops to 9, 12, cutting perplexity from 9.62 to 7.77.

Di He, Pengxiang Li, Da Chang, Qingyan Meng and 2 more

Published Oct 1, 2026 · 0 citations · ▲ 16 on Hugging Face · Code ★ 8

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arXivVideo-language models

OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction

OneStreamer unifies streaming video perception, memory, and proactive response via shared generation, achieving top results on eight benchmarks with a 4B model.

Xiangyu Zeng, Yuandong Yang, Zhiqiu Zhang, Yuhan Zhu and 20 more

Published Oct 1, 2026 · 0 citations · ▲ 232 on Hugging Face · Code ★ 169

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arXivVideo generation

Spatial Memory Intelligence: Endowing World Models with Understanding-Driven Long-Term Memory

Spatial Memory Intelligence introduces understanding-driven atomic operations for spatial-memory management in long-video world models, improving sparsity, stability, and spatial consistency.

Ying Yang, Guiyu Zhang, Lianghua Huang, Chang Nie and 4 more

Published Oct 1, 2026 · 0 citations · ▲ 49 on Hugging Face · Code ★ 19

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arXivInstruction tuning

Latent-MOPD: Latent Multi-Teacher On-Policy Distillation

Latent-MOPD distills multi-teacher LLM specialists via hidden-state and prediction-level on-policy supervision, outperforming token-only and representation-only baselines across math, code, and logic benchmarks.

Zhengyu Fang, Seoyeon Hong, Jie Yang, Muyang Li and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 63 on Hugging Face

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arXivVision-language-action models

World Action Modeling with Progressive Visual Planning

ProWAM predicts sparse visual sub-goals and actions via progressive planning, achieving state-of-the-art long-horizon robotic control and strong zero-shot real-world generalization.

Fei Zhang, Zhaochong An, Duncan Frost, Yikai Wang and 4 more

Published Oct 1, 2026 · 0 citations · ▲ 83 on Hugging Face

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arXivInstruction tuning

Local Support Learning

Local Support Learning pairs weight adapters with GMM gating to keep updates local, resolving catastrophic forgetting in LLMs up to 7B parameters without prior data.

Assaf Ben-Kish, Akarsh Kumar, James Glass, Raja Giryes

Published Oct 1, 2026 · 0 citations · ▲ 25 on Hugging Face · Code ★ 13

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69%Highly rated
arXivQuisqueyaQuincyLLM evaluation & benchmarks

RealCompanion: Benchmarking Human Understanding from Reasoning over Longitudinal Real-World Conversations

RealCompanion benchmarks AI companions on longitudinal real-world chats, finding needed past messages are usually recent, memory detectors fail on real messages, and persona reconstruction costs vary 31-fold at equal F1.

Arman Behnam, Sunglyoung Kim, Liangwei Yang

Published Oct 1, 2026 · 0 citations · ▲ 268 on Hugging Face

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arXivLLM agents & planning

VeriHarness: Scaling Agentic Verification for Long-Horizon Tasks

VeriHarness turns fixed base LLMs into agentic verifiers with workspaces and evidence tools, achieving top selection scores and 6.2, 6.4 point gains over single rollouts on long-horizon tasks.

Caiqi Zhang, Rujun Han, Zifeng Wang, Zoey CuiZhu and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 49 on Hugging Face · Code ★ 42

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arXivGeorgia Institute of TechnologyU California, Los AngelesU ChicagoMulti-agent LLM systems

Science Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystems

SciUtopia is a closed-loop LLM simulation framework modeling entire academic ecosystems; it finds resubmission amplifies reviewer burden, cautious exploration balances impact and diversity, and inequality can emerge without cumulative funding advantage.

Yiqiao Jin, Yiyang Wang, Lucheng Fu, Bing He and 7 more

Published Oct 1, 2026 · 0 citations · ▲ 40 on Hugging Face · Code ★ 29

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arXivCarnegie MellonLLM agents & planning

Selection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents

Selection-based Structured Reasoning replaces open-ended reasoning with selection among reusable candidates, cutting per-turn latency over 90% while matching leading small-model search agents' success rates.

Feiyu Gavin Zhu, Xiaoyu Zhu, Jiqi Yang, Rui Yang and 8 more

Published Oct 1, 2026 · 0 citations · ▲ 3 on Hugging Face · Code

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arXivRetrieval-augmented generation

AGO AI Quality Gate: Evidence-First Release Decisions for Retrieval-Augmented Generation

AGO is an evidence-first quality gate for RAG that treats judge errors and missing data as explicit outcomes, using stratified beta-binomial gates and mandatory meta-evaluation to reduce unsafe promotion to 22.2%-35.1% versus 29.3%-41.8% for naive gates.

Giulio Zeloni, Enrico Lo Conte, Salvatore Rionero, Giuseppe Santoro and 2 more

Published Oct 1, 2026 · 0 citations · ▲ 13 on Hugging Face

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arXivWeb & GUI agents

GUI-HARVEST: Self-Improving GUI Agents through Evidence-Driven Harness Evolution

GUI-HARVEST optimizes executable harnesses for frozen GUI agents by aligning visual effects, comparing task runs, and consolidating failure patterns into reusable source edits, improving OSWorld-Verified by up to 12.33 points.

Geyi Yang, Zikun Qu, Xiang Li, Zhiyong Wang and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 5 on Hugging Face · Code ★ 2

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arXivAgent benchmarks & environments

World Editing: Intervening on Executable Worlds at Increasing Depth

World editing intervenes on executable environments at increasing depth via IGMWorld and IGMBench, where top agents achieve 78.2% task success with reliability declining by depth.

Max Ku, Nok-Kan Law, Yu-Chien Tang, Shih-Ying Yeh and 14 more

Published Oct 1, 2026 · ▲ 14 on Hugging Face · Code

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 3/5
80%Must read
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arXivLLM agents & planning

ActiveSaddler: Automated Curriculum Learning for Agent Harness Optimization

ActiveSaddler automates curriculum learning for agent harness optimization via non-stationary bandits that adapt training scenarios to evolving failure patterns, boosting Pass@1 by 4.4, 7.5 points.

Sungho Park, Wonjoong Kim, Jue Zhang, Wook-Shin Han and 7 more

Published Oct 1, 2026 · ▲ 82 on Hugging Face

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5
86%Must read
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arXivExplainable AI

MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations

MEA is a multi-agent framework that uses reward-driven optimization to generate faithful natural-language explanations across tabular, text, and vision data, outperforming baselines by up to 34%.

Yuyang Cheng, R. Ravi, Srivarshinee Sridhar, Sriparna Saha and 2 more

Published Oct 1, 2026 · 0 citations · ▲ 4 on Hugging Face

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arXivAutomated scientific discovery

The AI Theorist reveals excitonic structure in $α$-RuCl$_3$

AI Theorist autonomously develops a first-principles model identifying distinct excitonic states with contrasting selection rules in α-RuCl3 optical spectra.

Hongjian Zhou, Xianfan Nie, Sean Wu, Tarun Patel and 4 more

Published Oct 1, 2026 · 0 citations · ▲ 3 on Hugging Face

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arXivRobot manipulation

OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor Policies

OpenRUA gives off-the-shelf coding agents only ROS 2 terminal access to act as zero-shot visuomotor policies, achieving 99% on CaP-Bench and 87% on LIBERO-PRO without bespoke harnesses or training, and reveals emergent perception and closed-loop control behaviors.

Zhaoyang Chu, Earl T. Barr, Claire Le Goues, Peter W. O’Hearn and 3 more

Published Oct 1, 2026 · 0 citations · ▲ 5 on Hugging Face · Code ★ 3

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arXivWeb & GUI agents

DeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents

DeskForge generates dense desktop supervision via controllable real-app environments, yielding 1.2M observations that improve GUI grounding and long-horizon computer-use task completion.

A. Said Gurbuz, Ahmed Nassar, Sunghwan Hong, Marc Pollefeys and 1 more

Published Oct 1, 2026 · 0 citations · ▲ 10 on Hugging Face · Code ★ 4

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arXivIn-context learning & prompting

Labels Override Definitions in Jev-Style Typed Decision Models

Typed decision models exhibit option-label bias because prompts prepend labels to definitions, letting label semantics override rules; removing labels or altering formatting fixes it.

Seyedarmin Azizi, Erfan Baghaei Potraghloo, Massoud Pedram

Published Oct 1, 2026 · 0 citations · ▲ 5 on Hugging Face

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arXivInstruction tuning

LLM2Jev: LLMs Are Already Jev-Style Decision Models -- When and How to Fine-Tune Them

LLM2Jev extracts calibrated Jev-style decisions from LLM token probabilities via training-free inference or tree-factorized fine-tuning, showing strong 4B models already match specialized decision models while fine-tuning mainly helps weaker backbones and specific tasks without degrading generation.

Yinheng Li, Justin Wagle

Published Oct 1, 2026 · 0 citations · ▲ 6 on Hugging Face

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arXivAgent benchmarks & environments

SimuVerity: Benchmarking Agents for Engineering-Grade Simulink Model Generation

SimuVerity benchmarks text-to-executable Simulink generation across engineering domains, finding best agents score only 42.86 and structural similarity poorly predicts engineering performance.

Ruiqi Zhang, Jiahao Wang, Mingxuan Li, Haichen Luo and 8 more

Published Oct 1, 2026 · ▲ 47 on Hugging Face · Code ★ 19

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
80%Highly rated
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ICML 2026WorkshopOffline RL

Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning

Decision Titan applies test-time training to offline RL, enabling long-term dependencies 20x beyond context windows and 1.7x length generalization while revealing time embeddings and encoding as critical factors.

Jude Waide, Robert Lieck

Published Oct 1, 2026 · 0 citations

100% Readers1 of 1 upvoted
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arXivAnomaly detection

Have an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series

An LLM autonomously searches for short NumPy anomaly detectors that lead the TSB-AD benchmark using spectral features and covariance-aware distances without neural networks or GPUs.

David Berghaus

Published Oct 1, 2026 · 0 citations

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