Good Papers

Trending

What readers here and on Hugging Face are upvoting

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

100% Readers1 of 1 upvoted
13/20 AI panelreviewers recommend it

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 2/5
84%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
78%Highly rated
?Highly ratedVote to see the score
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

100% Readers1 of 1 upvoted
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
90%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 3/5
78%Highly rated
?Highly ratedVote to see the score
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

100% Readers1 of 1 upvoted
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 4/10
strict 1/5
86%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
88%Must read
?Must readVote to see the score
arXivVision-language-action models

Taming VLAs under Robot Execution Errors: Self-Compensation and Stress Testing

Self-compensating VLA adapts online to robot execution errors via residual feedback, improving success over 30 points on physical arms and outperforming training-time robustness methods on RoboStress.

Sohyun Lee, Yoonjae Baek, Jaesang Won, Jinnyeong Kim and 4 more

Published Sep 29, 2026 · 0 citations · ▲ 18 on Hugging Face

100% Readers1 of 1 upvoted
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 3/5
91%Must read
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

100% Readers1 of 1 upvoted
16/20 AI panelreviewers recommend it

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
86%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 3/5
90%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
74%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
80%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
89%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 3/5
medium 6/10
strict 1/5
88%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 0/5
80%Must read
?Must readVote to see the score
arXivNew York University ShanghaiMechanistic interpretability

Making LLMs Say What They Think: Measuring and Improving CoT-Interpretability Alignment

We introduce CIA to measure chain-of-thought alignment with internal reasoning, finding low alignment that post-training improves substantially while maintaining accuracy.

Yihuai Hong, Shauli Ravfogel, Chen Zhao, Eunsol Choi

Published Sep 30, 2026 · 0 citations · ▲ 2 on Hugging Face · Code ★ 1

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5
89%Must read
?Must readVote to see the score
arXivKorea Advanced Institute of ScieEfficient inference & serving

SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving

SlimWise decouples MoE expert pruning across prefill and decode phases to boost serving throughput without sacrificing accuracy via direct KV cache reuse and selective distillation.

Gunho Park, Kyoungho Jeun, Juntaek Oh, Byeongjun Shin and 2 more

Published Sep 28, 2026 · 0 citations · ▲ 5 on Hugging Face

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score
arXivAmerican Rock Mechanics AssociatEmbodied agents

Adaptive Latent Capacity for World Models

ALeWM learns adaptive-width JEPA world models via MixSIGReg and prefix sampling, concentrating predictive information in early latent coordinates to improve planning with lower capacity.

Idan Achituve, Lior Dikstein, Idit Diamant, Arnon Netzer and 1 more

Published Sep 26, 2026 · 0 citations · ▲ 6 on Hugging Face

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 0/5
80%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 2/5
83%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
78%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 2/5
78%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
84%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score
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

100% Readers1 of 1 upvoted
7/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 7 of 20 reviewers recommend it
lenient 4/5
medium 2/10
strict 1/5
83%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 0/5
86%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5
71%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
6/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 6 of 20 reviewers recommend it
lenient 5/5
medium 1/10
strict 0/5
82%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 0/5
73%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Representation & contrastive learning

Structure-agnostic Causal Representation Learning

SaCRL 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 state

Arman Behnam, Binghui Wang

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published Oct 1, 2026 · 0 citations

0% Readers0 of 1 upvoted
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5
72%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
8/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 8 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 1/5
89%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
78%Highly rated
?Highly ratedVote to see the score
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

100% Readers1 of 1 upvoted
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
78%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 1/5
83%Must read
?Must readVote to see the score
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

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
78%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
82%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
78%Highly rated
?Highly ratedVote to see the score
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

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 1/5
71%Highly rated
?Highly ratedVote to see the score
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

0% Readers0 of 1 upvoted
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 0/5
90%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 3/5
88%Must read
?Must readVote to see the score
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

100% Readers1 of 1 upvoted
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5