Good Papers

Showing papers from Purdue University Show all papers

45%Niche pick
?Niche pickVote to see the score

Adaptive Residual Quantization for Memory-Efficient Temporal Action Segmentation

Gerard L Donahue, Guven Gergerli, Ayush Gupta, Reza Ghoddoosian and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Borda-Based Fair Multi-User Dueling Bandit in Tabular and Generalized Linear Settings

Maheed H Ahmed, Mahsa Ghasemi

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

A Theory of Adversary-Directed Online Learning

Steve Hanneke, Amirreza Shaeiri

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

Settling the Sample Complexity of Deterministic Agnostic PAC Learning

Shai Ben-David, Steve Hanneke, Farnam Mansouri, Amirreza Shaeiri

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
2/20 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.

45%Niche pick
?Niche pickVote to see the score

Optimizing Retraining Schedules via Learning Curves

Jin Sima, Changlong Wu, Ananth Grama, Wojciech Szpankowski

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

A Refined Sample-Complexity Analysis of Robust Policy Optimization under Decaying Actor Stepsizes

Swetha Ganesh, Vaneet Aggarwal

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Multi-Objective Causal Bandits: Minimal Intervention Space and Policy-Level Learning

Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026PurduePrivacy

Tail Wags the Model: Generalization and Membership Privacy Trade-offs of Sharpness-Aware Minimization

Young In Kim, Rajiv Khanna

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment

Rajdeep Haldar, Lantao Mei, Guang Lin, Yue XING and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Order-Optimal Sample Complexity for Distribution Learning via Flow Matching

Hari K Sahoo, Mudit G Gaur, Vaneet Aggarwal

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Reasoning Pathologies in Large Language Models: A Diagnostic Perspective

Rohan Surana, Junda Wu, Sheldon Yu, Gagan Mundada and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

$\gamma$-weakly $\theta$-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions

Mohammad Pedramfar, Vaneet Aggarwal

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

Breaking the $\sqrt{d}$ Communication Barrier in Federated Sampling with Adaptive Hamiltonian Monte Carlo

Jiajun Liang, Linxuan Wang, Guang Lin, Qifan Song

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 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.

57%Worth a look
?Worth a lookVote to see the score

Spectral Adaptive Repositioning for Flow-Based Single-Cell Perturbation Modeling

Shourya Verma, Mengbo Wang, Simran Kadadi, Shahin Mohammadi and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 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.

45%Niche pick
?Niche pickVote to see the score

StarCraft Motion: A Dataset for Agent Simulation in Adversarial and Partially Observable Scenarios

Yi-Chung Chen, Mingyu Kim, Ruqi Bai, James Z Hare and 2 more

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

– ReadersNo votes yet
0/20 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.

57%Worth a look
?Worth a lookVote to see the score

Rethink Action Chunking in VLA Through Human Motor Control

Wenxi Chen, Yuejiang Liu, Zijian He, Shaoshuai Mou and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Sticky Jump Diffusions: A Unifying Framework for Discrete, Continuous, and Hybrid Diffusion

Pascal J Dube, Patrick Pynadath, Jeremy Lu, Yuan Gao and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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.

57%Worth a look
?Worth a lookVote to see the score

OTel: Open Telco AI Datasets, Benchmarks, and Models

Farbod Tavakkoli, Gregory Diamos, Kenneth Church, David Kanter and 14 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

When, Where, What: Structural Guarantees for Travel Time Prediction on Temporal Graphs

Gabriel Buginga, Gabriel D Vilela, Jincheng Zhou, Mohit Tawarmalani and 1 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

A Frank-Wolfe Approach to Goldstein Stationarity

Swati Padmanabhan, Zitao Song, Zhe Zhang

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

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Talk Less, Work More: Communication-Efficient Decentralized Stochastic Approximation

Tianyu Cao, Haixiang Sun, Yang Xu

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs

Zian Su, Ziyang Huang, Kaiyuan Zhang, Xiangyu Zhang

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Marginal-Nonuniform Multiclass Learning

Nataly Brukhim, Steve Hanneke, Amirreza Shaeiri, Maximilian Thiessen

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Improving Context-Shift Robustness of Convolutional Networks via Context-Regularized Cross-Entropy

Jinen Setpal, Chaoyue Liu

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Split and Bridge: Multimodal Generation via Diffusion Bridging

Ahmad Arrabi, Xiaohan Zhang, Xingyu Li, Safwan Wshah

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

A Locality-Aware Surrogate for Natural-Gradient Descent in Quantum Optimization

Md Mobasshir Arshed Naved, Wenbo Xie, Wojciech Szpankowski, Ananth Grama

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Statistical Matching via Schr\"odinger Bridge beyond Conditional Independence

Eunho Koo, Jinwon Sohn, Tongseok Lim

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning

Feijie Wu, Weiwu Zhu, Yuxiang Zhang, Soumya Chatterjee and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Hierarchical Graph Alignment for Cross-Modal 3D Scene Grounding

Tianyi Shang, Zhenyu Li

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Enabling Preference-driven Unlearning in Few-step Distilled Text-to-Image Diffusion Models

Gaurav Patel, Jun Fang, Greg Ver Steeg, Qiang Qiu and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Stable GFlowNets with Probabilistic Guarantees

Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal, Ruoyu Song and 5 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Beyond Flat Gossip: Tiered Gossip Learning for Scalable Collaborative AI

Atul Sharma, Kavindu Herath, Saurabh Bagchi, Chaoyue Liu and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
71%Highly rated
?Highly ratedVote to see the score

Persistent-Transient Policy Evaluation for Markov Chains via Minimal Peripheral Quotients

Quotienting Markov chains by their peripheral invariant subspace separates persistent regime profiles from transient dynamics for stable policy evaluation.

Yang Xu, Vaneet Aggarwal

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
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.

76%Highly rated
?Highly ratedVote to see the score

Probabilistic Signature Inversion: Learning Conditional Distributions from Truncated Signatures

Truncated signature inversion is reframed as learning conditional path distributions via signature-conditioned flow matching, with derived Bayes error baselines and validated reconstruction on real data.

Junoh Kang, Kiseop Lee, Bohyung Han

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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
80%Must read
?Must readVote to see the score

Ultra Fast PDE Solving via Physics Guided Few-step Diffusion

Phys-Instruct distills diffusion PDE solvers into few-step generators with explicit physics guidance, achieving orders-of-magnitude faster inference and over 8x lower PDE error.

Xiangrui Cindy Kong, Yueqi Wang, Haoyang Zheng, Weijian Luo and 1 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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.

80%Must read
?Must readVote to see the score

When the Same Coefficients Reach Different Places: Asymmetric Realizability in Transplanting Tokenizers across Large Language Models

Cross-vocabulary tokenizer transplantation exhibits asymmetric realizability, allowing identical reconstruction coefficients to stay inert in donor anchors yet yield high-salience outputs in base anchors, forming breaker tokens that survive weight merging and evade spectral filters and LoRA mitigati

Xiaoze Liu, Weichen Yu, Matt Fredrikson, Xiaoqian Wang and 1 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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.

83%Must read
?Must readVote to see the score

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

AgentForesight introduces online trajectory auditing that predicts multi-agent failures during execution, with a 7B model outperforming GPT-4.1 and DeepSeek-V4-Pro by up to 19.9% with 3x lower step error.

Boxuan Zhang, Jianing Zhu, Zeru Shi, Dongfang Liu and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 7 on Hugging Face · Code ★ 19

– 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.

83%Must read
?Must readVote to see the score

Mitigating Retaliatory Algorithmic Collusion in Repeated Games

CURB penalizes policy dependence on defection histories via total-variation reward shaping to eliminate collusive equilibria in repeated multi-agent games.

Karthik Sivachandran, Rohan Paleja

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

– 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.

89%Must read
?Must readVote to see the score

Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective

Existing plasticity diagnostics fail to predict trainability, but optimization readiness, combining gradient strength and reliability, lower-bounds optimization gain and predicts plasticity more reliably.

Jiuqi Wang, Jayanth Srinivasa, Claire Chen, Shuze D Liu and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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.

83%Must read
?Must readVote to see the score

SEED: Self-Speculative Decoding via Implicit Encoder–Decoder

SEED reinterprets decoder-only transformers as implicit encoder-decoders to reuse deep representations for fast self-speculative drafting, achieving up to 2.7x speedup.

Hankun Lin, Patrick Pynadath, Ruqi Zhang

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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.

86%Must read
?Must readVote to see the score

Contrastive Representation Shaping for LLM Unlearning

CLReg uses contrastive regularization to separate forget and retain representations, reducing entanglement and improving LLM unlearning without extra privacy risks.

Haoran Tang, Rajiv Khanna

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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.

88%Must read
?Must readVote to see the score

SARL: Label-Free Reinforcement Learning by Rewarding Reasoning Topology

SARL improves reasoning via label-free reinforcement learning that rewards reasoning topology over outcomes, outperforming supervised and preference-based methods on math and open-ended tasks with more stable training.

Yifan Wang, Bolian Li, David Cho, Ruqi Zhang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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.

80%Must read
?Must readVote to see the score

Diff-Instruct with Diffused Reward: Towards Principled One-step Generator RL

DIDR aligns one-step generators via trajectory-level diffusion reward propagation, avoiding fidelity loss to Pareto-dominate SDXL and surpass 50-step teachers in one step.

Junyi Wu, Weijian Luo, Haoyang Zheng, Ruizhe Zhang and 1 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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.

86%Must read
?Must readVote to see the score

CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers

CORP uses closed-form ridge regression to recover representations and prune transformer structures without retraining, retaining 83.27% ImageNet accuracy at 50% sparsity.

Boxiang Zhang, Baijian Yang

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 5/5
medium 8/10
strict 1/5
80%Must read
?Must readVote to see the score

Towards Reliable LLM Evaluation: Correcting the Winner’s Curse in Adaptive Benchmarking

SIREN corrects adaptive LLM evaluation's winner's curse via splitwise selection and bootstrap inference for reliable procedure-level performance estimates.

Yang Xu, Jiefu Zhang, Haixiang Sun, Zihan Zhou and 2 more

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

– 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.

91%Must read
?Must readVote to see the score

On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation

On-Policy Consistency Training improves LLM safety across sycophancy, jailbreaks, and safety awareness while avoiding the capability regressions of supervised fine-tuning.

Andy Q Han, Kristina Fujimoto, Avidan Shah, Kiet Nguyen and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
17/20 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.

80%Must read
?Must readVote to see the score

Failing to Falsify: Evaluating and Mitigating Confirmation Bias in Language Models

LLMs exhibit confirmation bias by proposing confirming triples rather than falsifying hidden rules, reducing discovery rates, though prompting counterexample consideration improves success from 42% to 56%.

Ayush Rajesh Jhaveri, Anthony GX-Chen, Ilia Sucholutsky, Eunsol Choi

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– 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.

78%Highly rated
?Highly ratedVote to see the score

Improving the Efficiency of Language Agent Teams with Adaptive Task Graphs

LATTE coordinates LLM teams via shared evolving task graphs that reduce tokens, time, and conflicts while matching or exceeding baseline accuracy.

Elizabeth Mieczkowski, Alexander Ku, Tiwalayo Eisape, Dilip Arumugam and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · Code ★ 6

– 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.

74%Highly rated
?Highly ratedVote to see the score

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting

Multiclass PAC learning with bandit feedback is characterized by the new bandit DS dimension via pseudo-boxes, yielding sharp sample complexity scaling with total neighbors.

Steve Hanneke, Qinglin Meng, Shay Moran, Amirreza Shaeiri

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 1/5
medium 5/10
strict 3/5
86%Must read
?Must readVote to see the score

Communication-Efficient Personalized Adaptation via Federated-Local Model Merging

Potara merges federated and local models via closed-form optimal weights to improve federated personalization with lower communication costs.

Yinan Zou, Md Kamran Chowdhury Shisher, Christopher Brinton, Vishrant Tripathi

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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 9/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026PurdueDeep RL

Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework

Natural policy gradient equals doubly smoothed policy iteration, a Bellman-operator framework achieving global geometric convergence and O((1-γ)^{-1} log ε^{-1}) iteration complexity without modified stepsizes or regularization.

Phalguni Nanda, Zaiwei Chen

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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.

76%Highly rated
?Highly ratedVote to see the score

Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns

SkillMigrator learns reusable web skills via transferable interaction patterns matched by layout similarity to reduce LLM actions 8-10% across WebArena and Mind2Web.

Shiqi He, Yue Cui, Feijie Wu, Xinyu Ma and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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.

80%Must read
?Must readVote to see the score

CORVUS: Context Optimization and Reduction Via Underlying Synchronization for LLM Coding Agents

CORVUS decouples file reads from observations via synchronized registries, cutting input tokens by 9-50% and reasoning cycles by up to 37% while preserving pass rates.

Mingwei Zheng, David OBrien, Siwei Cui, Pardis Pashakhanloo and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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.

72%Highly rated
?Highly ratedVote to see the score

A Statistical Theory of Gated Attention through the Lens of Hierarchical Mixture of Experts

Gated attention represents attention matrices as hierarchical mixtures of experts and achieves polynomial sample complexity versus exponential for multi-head self-attention.

Viet Nguyen, Thinh Cao, Tuan M Pham, Tan Dinh and 3 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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.

89%Must read
?Must readVote to see the score

ThousandWorlds: A benchmark for climate emulation of potentially habitable exoplanets

ThousandWorlds introduces a multi-model exoplanet climate benchmark of ~1,700 GCM simulations, showing Gaussian processes outperform deep learning in low-data multi-simulator regression.

Edward Stevenson, Mei T Mak, Eric Wolf, Denis E Sergeev and 3 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 1 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 8/10
strict 3/5
88%Must read
?Must readVote to see the score

Learning Visual Feature-Based World Models via Residual Latent Action

Residual Latent Action predicts visual feature dynamics via flow matching, outperforming diffusion world models with orders-of-magnitude faster inference and enabling offline robot learning from videos.

Xinyu Zhang, Zhengtong Xu, Yutian Tao, Yeping Wang and 2 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 47

– 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.

78%Highly rated
?Highly ratedVote to see the score

On the Token Value Inequality in Efficient Reasoning

Token value inequality in reasoning traces enables identifying core versus redundant tokens via log probabilities, yielding 76% token reduction with preserved accuracy via selective compression.

Runjia Zeng, Hang Hua, Yiyang Liu, Zhiqiang Tao and 4 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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 7/10
strict 0/5
80%Must read
?Must readVote to see the score

Sponsored Questions and How to Auction Them

Formal model for auctioning LLM clarifying prompts compares joint VCG optimization with decoupled modular mechanisms, finding joint design achieves efficiency and truthfulness while modular approaches suffer unbounded strategic inefficiency.

Kshipra Bhawalkar, Alexandros Psomas, Di Wang

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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 5/10
strict 2/5
74%Highly rated
?Highly ratedVote to see the score

Coreset-Induced Conditional Velocity Flow Matching

CCVFM replaces isotropic noise with a coreset-derived Gaussian mixture source for hierarchical rectified flow, using a lightweight correction flow for residuals to achieve competitive few-step generation.

Xiao Wang, Zihua She, Jianxi Su

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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 2/5
medium 6/10
strict 1/5
89%Must read
?Must readVote to see the score

Multi-site PPG: An In-the-Wild Physiological Dataset from Emerging Multi-Site Wearables

Multi-site PPG is an in-the-wild dataset of 350+ hours from earring, ring, watch, and necklace wearables, showing heart-rate errors vary substantially by body site.

Jiayi Shao, Jiaying Ye, ShengYao Liu, Zachary Englhardt and 3 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 7/10
strict 4/5
71%Highly rated
?Highly ratedVote to see the score

Oracle-Robust Online Alignment for Large Language Models

Under misspecified preference oracles, online LLM alignment minimizes a worst-case objective that decomposes into loss plus a sensitivity penalty, with projected updates achieving near-optimal complexity.

Zimeng Li, Mudit G Gaur, Vaneet Aggarwal

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
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 2/5
medium 3/10
strict 2/5
88%Must read
?Must readVote to see the score

Breaking the Bias Barrier in Concave Multi-Objective Reinforcement Learning

Concave scalarized multi-objective RL suffers biased gradients that cause O(ε⁻⁴) sample complexity; multi-level Monte Carlo NPG achieves optimal O(ε⁻²).

Swetha Ganesh, Jason Chia, Vaneet Aggarwal

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 7/10
strict 4/5
80%Must read
?Must readVote to see the score

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

StreamGaze introduces a benchmark for evaluating gaze-guided temporal and proactive reasoning in streaming videos, revealing large performance gaps between state-of-the-art MLLMs and humans.

Daeun Lee, Subhojyoti Mukherjee, Branislav Kveton, Ryan Rossi and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 8 on Hugging Face · Code ★ 28

– 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
78%Highly rated
?Highly ratedVote to see the score

Analytical Correction for Subsampling Bias in Drifting Models

Analytical Bias Correction fixes O(1/n) minibatch centroid bias in drifting models via a closed-form plug-in, reducing it to O(1/n²) with negligible overhead and improving CIFAR-10 FID.

Jiaru Zhang, Zeyun Deng, Juanwu Lu, Ziran Wang and 1 more

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

– 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 3/5
medium 7/10
strict 1/5
71%Highly rated
?Highly ratedVote to see the score

Differentiable Belief-based Opponent Shaping

D-BOS differentiates through k-step softmax-Bayes belief dynamics to shape multi-agent opponent beliefs, outperforming PPO and BBM in hidden-role games.

Aarav G Sane, Karthik Sivachandran, Rohan Paleja

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
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 3/5
medium 4/10
strict 0/5
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026PurdueAgent memory

MEMAUDIT: An Exact Package-Oracle Evaluation Protocol for Budgeted Long-Term LLM Memory Writing

MEMAUDIT provides an exact package-oracle protocol isolating budgeted long-term memory writing via certified finite optimization, separating representational quality and validity preservation from retrieval and reasoning effects.

Nishant Bhargava, Rodrigo S Barrento

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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
74%Highly rated
?Highly ratedVote to see the score

Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion

Orthrus unifies autoregressive and diffusion views in transformers to enable lossless parallel token generation with up to 7.8x speedup and O(1) memory overhead.

Van Chien Nguyen, Chaitra Hegde, Van-Cuong Pham, Ryan Rossi and 2 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 12 on Hugging Face · Code ★ 482

– 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 4/5
medium 4/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score

Instructing LLMs to Negotiate using Reinforcement Learning with Verifiable Rewards

RLVR trains a 30B LLM buyer via verifiable economic rewards to negotiate, revealing four-phase strategic evolution and outperforming much larger frontier models in surplus extraction.

Shuze D Liu, Claire Chen, Jiabao S Xiao, Lei Lei and 3 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 3/10
strict 2/5
78%Highly rated
?Highly ratedVote to see the score

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning

NASDAQ normalizes low-dimensional observations to balance dynamics prediction losses and couples value learning with short-term value and next-observation prediction, achieving strong sample efficiency and faster training across diverse domains.

Xinwei Liu, Junyuan Liang, Zicong Hong, Jianting Zhang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– 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 7/10
strict 0/5
88%Must read
?Must readVote to see the score

Objective Shaping with Hard Negatives: Windowed Partial AUC Optimization for RL-based LLM Recommenders

GRPO for LLM recommenders maximizes AUC but beam-search negatives reshape objectives toward partial AUC; proposed WPAUC with TAWin optimization improves top-K alignment and achieves state-of-the-art results.

Wentao Shi, Qifan Wang, Chen Chen, Fei Liu and 6 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

– 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 8/10
strict 3/5
71%Highly rated
?Highly ratedVote to see the score

The Query Complexity of Local Search in Rounds on General Graphs

This paper bounds the query complexity of multi-round local search on general graphs, proving deterministic upper and randomized lower bounds that extend grid results to arbitrary connected graphs.

Simina Branzei, Ioannis Panageas, Dimitris Paparas

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– 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 3/5
medium 2/10
strict 1/5
78%Highly rated
?Highly ratedVote to see the score

Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions

MAPs introduces a mini amusement-park simulator benchmarking integrated business decision-making, finding experts outperform state-of-the-art agents by over 11x due to weaknesses in long-horizon planning, sample-efficient learning, and spatial reasoning.

Stéphane Aroca-Ouellette, Ian Berlot-Attwell, Panagiotis Lymperopoulos, Abhiramon Rajasekharan and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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
91%Must read
?Must readVote to see the score

MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI

MLS-Bench evaluates AI agents on inventing scalable ML methods across 140 tasks, finding current systems fail to reliably surpass human-designed approaches due to insufficient scientific validation insight.

Bohan Lyu, Yucheng Yang, Siqiao Huang, Jiaru Zhang and 24 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 8 on Hugging Face · Code ★ 120

– ReadersNo votes yet
17/20 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: 17 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 4/5
74%Highly rated
?Highly ratedVote to see the score

Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks

A feasibility-preserving graph neural network replaces SDP solvers in exact Max-Cut branch-and-bound, cutting bounding costs up to 10.6× versus Mosek.

Hao Chen, Chendi Qian, Christopher Morris, Andrea Lodi and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– 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 3/5
medium 5/10
strict 1/5