Good Papers

Showing Deep RL Show all papers

76%Highly rated
?Highly ratedVote to see the score
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

– 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 7/10
strict 0/5
83%Must read
?Must readVote to see the score
arXivDeep RL

Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints

The Homomorphic Advantage Operator stabilizes FHE-based reinforcement learning by centering TD targets to eliminate Bellman drift, achieving zero approximation-bound breaches and 18-point accuracy gains without extra multiplicative depth.

Abid Mohamed Nadhir, Ahmad Al Hanbali, Beggas Mounir

Published Oct 1, 2026 · 0 citations

– 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.

76%Highly rated
?Highly ratedVote to see the score
arXivDeep RL

iADD: Improving Alignment and Diversity in Diffusion Policy Optimization

iADD analyzes diffusion policy optimization to show only-latter-timestep updates harm diversity, then proposes incremental Feynman-Kac training that improves alignment-diversity tradeoffs across tasks.

Ashok Prasad Neupane, Saugat Adhikari, Pramish Paudel, Ajad Chhatkuli and 1 more

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

– 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.

83%Must read
?Must readVote to see the score
arXivHuawei TechnologiesImperial College LondonUniversity College LondonDeep RL

Tail-Influence Sampling for CVaR Policy Evaluation

Tail-Influence Sampling allocates evaluation budgets by tail influence to estimate CVaR with oracle variance and lower MSE than rollouts.

Pauline Bourigault, Xiaotong Ji, Matthieu Zimmer, Rasul Tutunov and 1 more

Published Sep 29, 2026 · 0 citations · ▲ 23 on Hugging Face · Code ★ 1

– 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.

74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026DeepMindDeep RL

Delightful Distributed Policy Gradient

Delightful Policy Gradient gates distributed updates with delight (advantage times surprisal) to suppress high-surprisal failures while preserving rare successes, outperforming importance-weighted methods under staleness, bugs, and corruption.

Ian Osband

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

0% Readers0 of 1 upvoted
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 3/5
medium 10/10
strict 3/5
90%Must read
?Must readVote to see the score
NeurIPS 2026Can Tho University and VinUniverCan-ThoVinUniversityU AizuDeep RL

Modeling quantum neural network gradient with reinforcement learning

RLQ-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.

Nhan Luu, Trung D Luu, Ngoc Nam Pham, Thang C Truong

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

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 4/5
medium 8/10
strict 3/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Xi'an JiaotongShanghai University of Finance aThe Chinese University of Hong KSGIT AIA*STARDeep RL

A Primal-dual Approach for Semi-Infinitely Constrained Reinforcement Learning

Di Wang, Liangyu Zhang, Haishan Ye, Guang Dai and 1 more

Sydney Poster Session 6, Thu, Dec 10, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026XidianDeep RL

Reinforcement Learning for View-Adaptive Distillation in 3D Gaussian Compression

Hongji Zhao, Mingrui Zhu, Xin Wei, Nannan Wang

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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U California, San DiegoUC San DiegoDeep RL

Safe Score Matching: Diffusion Policies with Hamilton-Jacobi Reachability for Online Safe Reinforcement Learning

Boyang Li, Matthew Kim, Sylvia Herbert

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · 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
NeurIPS 2026The Ohio StateDeep RL

Finite-Memory Control of POMDPs: Fundamental Limits and Efficient Design

Emrecan Kutay, Atilla Eryilmaz, Ness Shroff

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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U Wisconsin-MadisonU Wisconsin - MadisonU Wisconsin -- MadisonDeep RL

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling

Nicholas Corrado, Wenyuan Huang, Josiah Hanna

Sydney Poster Session 2, Tue, Dec 8, 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
NeurIPS 2026Shanghai JiaotongCentral SouthSensetimeThe Chinese University of Hong KSenseTimeDeep RL

ROLLVERIFY: BRIDGING EFFICIENCY AND ACCURACY IN LONG-TAIL ROLLOUT REINFORCEMENT LEARNING

Yongqiang Yao, Jingru Tan, Kaihuan Liang, Zixin Yin and 4 more

Sydney Poster Session 1, Tue, Dec 8, 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Pusan NationalDeep RL

Accelerating Safe Reinforcement Learning with Massive Parallelism

Joonyoung Lim, Younghwan Yoo

Sydney Poster Session 2, Tue, Dec 8, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Wisconsin–MadisonU Wisconsin - MadisonDeep RL

When Does Knowing the State Help? Diagnosing Process vs. Outcome Reward Design

Wenpei Shao, Ross Jacobucci

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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Science and Technology of ChinThe Hong Kong University of ScieMohamed bin Zayed University of Hong Kong PolytechnicHKBU / RIKENDeep RL

Interactive Combinatorial Reinforcement Learning for Knowledge Graph Reasoning

Jun Nie, Yonggang Zhang, Tongliang Liu, Chengqi Zhang and 2 more

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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026DalhousieDeep RL

Instability of Meta-Learning Intrinsic Rewards for Policy Gradient Reinforcement Learning

Dilith Jayakody, Domenic Rosati, Janarthanan Rajendran

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 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
NeurIPS 2026Pusan NationalDeep RL

LOCU: Löwdin-Orthogonalized Constraint Updates for Multi-Constraint Policy Optimization

Joonyoung Lim, Younghwan Yoo

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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Renmin University of ChinaSUN YAT-SEN UNIVERSITYU the Chinese Academy of ScienceTsinghuaDeep RL

Exploring Lifelong Adaptation: In-Context Reinforcement Learning in Non-Stationary Environments

Ye Wang, Kaiqian Cui, Xinrun Xu, Tao Zhang and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026TU DarmstadtDeep RL

Cross-Question Reliable Reinforcement Learning

Hector G. Rodriguez, Marcus Rohrbach

Sydney Poster Session 3, Wed, Dec 9, 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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026ML & Alignment Theory ScholaGoogle DeepMindDeep RL

Designing Effective Monitor-Based Interventions for Mitigating Reward Hacking During RL

Aria Wong, Joshua Engels, Neel Nanda

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 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.

AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026d_modelML & Alignment Theory ScholaStanfordMATS ResearchGoogle DeepMindDeep RL

Gradient Routing Localizes and Removes Unintended Behaviors in RL

Jake Ward, Shawn Hu, Aria Wong, Nathan Hu and 3 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Indian Institute of Technology, PurdueDeep RL

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
NeurIPS 2026Carnegie MellonCMU, Carnegie MellonSchool of Computer Science, CarnDeep RL

Implicit Goal Conditioning via Value Disaggregation

Shashwat Saxena, Mehul Goel, Sreyas Venkataraman, Sarvesh Patil and 1 more

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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U California, Santa BarbaraU California, Santa CruzU ChicagoVirtue AI, University of California, SantDeep RL

NitroBox: Lightning-Fast Sandbox for Large-Scale RL Training

Yuzhou Nie, Ruilin Zhou, Zhaorun Chen, Jingyang Zhang and 5 more

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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Tsukuba, TsukubaU TsukubaLY Corp.U Tsukuba / RIKEN AIPDeep RL

Reward-Estimated Hypergradient for Bilevel Reinforcement Learning with Black-Box Follower

Shigeki Kusaka, Mikoto Kudo, Takumi Tanabe, Akifumi Wachi and 1 more

Sydney Poster Session 3, Wed, Dec 9, 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U Massachusetts AmherstDepartment of Computer Science, Deep RL

Uncertainty-Guided Reward Labeling for Reinforcement Learning under Limited Feedback

Renhao Zhang, Shreyas Chaudhari, Bruno Silva

Atlanta Poster Session 2, Wed, Dec 9, 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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Tsinghuanational university of singaore,U Science and Technology BeijingDeep RL

Bootstrapped Bipartite Actor-Critic for Diffusion RL

Tianze Zhu, yinuo Wang, Letian Tao, Tianyi Zhang and 5 more

Sydney Poster Session 1, Tue, Dec 8, 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
NeurIPS 2026QiyuanlabBeijing Institute of TechnologyQiyuan LabAcademy of Military SciencesDeep RL

EDEN: Emergent Dynamics in Evolutionary Neural-networks for Robust Continuous Control

Chi Zhang, Jinge Li, Yifei Wang, Lei Wang and 1 more

Sydney Poster Session 3, Wed, Dec 9, 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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026HKUSTHong Kong University of Science Department of Computer Science aThe Hong Kong University of ScieThe Hong Kong University of ScieDeep RL

CPA: Efficient and Stable FP4 RL Training via Cross-Precision Alignment

Gu Gong, Yining Wei, Yuechen Tao, Tianyuan Wu and 10 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.

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
NeurIPS 2026China University of PetroleumChina University of Petroleumchina university of petroleumHuazhong University of Science aDeep RL

Mitigating Compounding Errors in Online Reinforcement Learning via Optimal Transport Regularized Flow Matching

Boxiang Tao, Lei Guo, Bin Wang, Zexin Wang and 1 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.

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
NeurIPS 2026Weill Cornell Medicine, CornellCornellDeep RL

On-Policy Hindsight Distillation for Early Risk Prediction

Qiannan Zhang, Fei Wang

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.

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
NeurIPS 2026U Illinois Urbana-ChampaignUIUCGoogle ResearchU Illinois at Urbana-ChampaignU Illinois, Urbana ChampaignDeep RL

RL-Inf: Tracking Non-local Training Data Influence for Online Reinforcement Learning

Shixuan Liu, Cheng Tang, Yuzheng Hu, Fan Wu 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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Hanoi University of Science and Deep RL

BECON: Belief-Conditioned Constrained Multi-Objective Reinforcement Learning under Drifting Preferences and Budgets

Bui Trong Duc, Huynh Thi Thanh Binh

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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026TianjinMontreal Institute for Learning ShanxiDeep RL

What Kind of Diffusion Models Do We Need in Online Reinforcement Learning?

Zihao Wu, Hongyao Tang, Yi Ma, YAN ZHENG 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.

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
NeurIPS 2026Beijing JiaotongU Electronic Science and TechnolInstitute for AI Industry ResearHorizon RoboticsCarizonDeep RL

Higher-Order Action Supervision Makes A Strong Policy Class

Peng Cheng, Yunxian Hou, Zhi Zhou, Qian Zhang and 2 more

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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Korea Advanced Institute of ScieKAISTDeep RL

Towards a Unified Model for Flexible Job Shop Scheduling Problems

Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, Hyun-Jung Kim

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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
NeurIPS 2026Mila - Quebec Artificial IntelliUniversitat Pompeu FabraMila, Université de MontréalMila - Quebec Artificial IntelliU MontrealDeep RL

A Surrogate Perspective on Convergence of Fixed-Target DQN

Zichu Liu, Nneka M Okolo, Ryan D'Orazio, Danilo Vucetic and 2 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026TulaneDeep RL

Behavior-Discriminative Reward Shaping for Reward-Robust Reinforcement Learning

Zixuan Liu, Fangzheng Wu, Brian Summa, Zizhan Zheng

Sydney Poster Session 1, Tue, Dec 8, 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
NeurIPS 2026DGISTDaegu Gyeongbuk Institute of SciKorea Advanced Institute of ScieDeep RL

H-GenPO: Hierarchical Generative Policy Optimization via the Option-Critic Framework

Wonhyeok Choi, Minwoo Choi, Jaeyeul Kim, Kyumin Hwang and 2 more

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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026ShenzhenShenzhen Technology University, Shenzhen TechnologyTencent AI LabDeep RL

Foundation Pareto Flow Policy for Multi-Objective Reinforcement Learning

Zhanjiang Yang, Lijun Sun, Yueming Li, Meng Li 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026École PolytechniqueHuawei Technologies Ltd.Shenzhen Research Institute of BDeep RL

Adaptive Scheduling Pipeline For Multi-Instance Asynchronous Reinforcement Learning

Salah Chikhi, Luis H Ruiz, Entong Li, Li Zeng

Paris Poster Session 1, Wed, Dec 9, 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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026XiamenU YorkDeep RL

DGRAF: Observation-Quality-Aware Reinforcement Learning for Dynamic Reconfigurable Batteries

Jiasong Chen, Jingwei Hu, Zheng Fang, Zhihong Zhang

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026The Hong Kong University of ScieNanjingTencent AI LabU Science and Technology of ChinTongjiDeep RL

Canopy: Tree-Aware Rollout Scheduling for Agent Reinforcement Learning

Feiyuan Zhang, LI Pengbo, Ziniu Li, Yuhao Jiang and 8 more

Sydney Poster Session 6, Thu, Dec 10, 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
NeurIPS 2026TsinghuaTsinghua University, TsinghuaNankaiBeijing UnionAlibaba GroupDeep RL

Feasible Policy Optimization for Safe Reinforcement Learning

Yujie Yang, Yuanxu Sun, Wenyu Li, Beiyan Jiang and 2 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.

67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026The Hong Kong PolytechnicMcGill University & Mila - QHong Kong PolytechnicTongji universityTongjiDeep RL

Preference-Guided Adversarial Policy Optimization for Long-Tail Robust Driving

Tong Nie, Yihong Tang, Junlin He, Yuewen Mei and 4 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Southeast University ShSoutheastU Nottingham Ningbo ChinaImperial College LondonDeep RL

Reconciling Operational Energy Trilemma: A Heterogeneous Risk-Constrained MDP Framework with Residual Policy Learning

Yujian Ye, Siqi Qian, Yizhi Wu, Tianxiang Cui and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 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
NeurIPS 2026Alberta Machine Intelligence InsU AlbertaDeep RL

Learning Reusable Options by Decomposing Neural Policies

Parnian Behdin, Reza Abdollahzadeh, Kiarash Aghakasiri, Levi Lelis

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 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
NeurIPS 2026Northwestern PolytechnicalThe Chinese University of Hong KZhejiangXi'an University of Posts aDeep RL

S$^2$-RL: Sample-Set Dual Reinforcement Learning for Generative Semantic Segmentation Dataset Distillation

Haoyu Wang, Fei Zhou, Qingqing Qiu, Lei Zhang and 2 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Florida AtlanticDeep RL

Grouped Adaptive Head Mixing for Personalized Multi-Task Federated Reinforcement Learning

Yiran Pang, Zhen Ni, Dimitris Pados, Xiangnan Zhong

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
NeurIPS 2026U OxfordU WarwickDeep RL

Subprocess-Constrained Markov Decision Processes

Jiarui Gan, Debmalya Mandal

Sydney Poster Session 3, Wed, Dec 9, 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
NeurIPS 2026BostonBoston University / Broad InstitDeep RL

Learning to Undo: Transfer Reinforcement Learning under State Space Transformations

Mridul Mahajan, Aldo Pacchiano, Xuezhou Zhang

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Institute of automation, ChineseInstitute of Automation, ChineseCASIADeep RL

Distribution-Adaptive Policy Optimization

Yuxiao He, Ziqi Wang, Xingzhou Lou, Xiaoqian Liu and 1 more

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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Texas A&M University - ColleCSAIL, MITGoogle Deepmind / HarvardHarvardDeep RL

Iterative Gumbel Planning for Continuous Control

Shaohuai Liu, Weirui Ye, Yilun Du, Le Xie

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
NeurIPS 2026Beijing JiaotongBeijing jiaotong univercityDeep RL

Decoupling is the Key: Scaling Deep Value Networks in Reinforcement Leanring

Yunsheng Xue, Ziyi Zhang, zhihao wu, Youfang Lin

Sydney Poster Session 6, Thu, Dec 10, 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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Hong Kong PolytechnicThe Hong Kong PolytechnicThe University of TokyoUNSW SydneyDeep RL

Discovering Programmatic Policies from Reinforcement Learning-Based Traffic Signal Controllers

Lindong Xie, Yang Zhang, Beiyu Song, XING Zeren and 2 more

Sydney Poster Session 2, Tue, Dec 8, 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
NeurIPS 2026Google ResearchGoogle Research & Courant InResearch Scientist, Google ReseaDeep RL

SAMPPO: Structure-Aware Mirror Proximal Policy Optimization

Corinna Cortes, Mehryar Mohri, Yutao Zhong

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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Beijing Institute of MathematicaCapital NormalDeep RL

Physics-Informed Optimal Control by Control-Only Supervision with Error Guarantees on Value and Policy

Zihua Wang, Xiaopei Jiao, Yunfeng Cai

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
NeurIPS 2026BocconiPolitecnico di MilanoDeep RL

Constrained MDPs with Trajectory Constraints

Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 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
NeurIPS 2026SpotlightSeoul NationalDeep RL

Distributionally Robust Domain Randomization with Learned Risk-Sensitive Dynamics Samplers

Sukchul Jeong, Insoon Yang

Sydney Poster Session 6, Thu, Dec 10, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Universitat Pompeu FabraDeep RL

Solving Stochastic Control under Multiplicative and Internal Noise via Constrained Optimization

Ruben Moreno Bote, Francesco Damiani, Dmytro Grytskyy

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026UC Berkeley, University of CalifU California, BerkeleyUC BerkeleyDeep RL

Learning Process Rewards via Visitation Matching for Efficient RL

Raymond Tsao, Andrew Wagenmaker, Sergey Levine

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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U LuxemburgBeijing Institute of TechnologyU the Sunshine CoastDeep RL

Prevailing Bisimulation Metric Learning Is Biased: Implicit Regularization and Its Remedy

Junqi Lu, Ruixiang Sun, Xin Li, Gaopeng Peng and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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 0/5
medium 0/10
strict 1/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U Wisconsin - MadisonDepartment of Computer Science, UW-MadisonDeep RL

Anatomy of Off-Policy Policy Gradient: Importance Sampling, KL Regularization, and Baselines

Haoqun Cao, Yurun Yuan, Tengyang Xie

Sydney Poster Session 2, Tue, Dec 8, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Huazhong University of Science aThe Hong Kong University of ScieU Hong KongHong Kong University of Science Deep RL

The Cost of Mismatch: Noise Amplification in Zeroth-Order Reinforcement Learning

Lianmin Chen, Junbin Qiu, Chenxing Wei, Yao SHU and 1 more

Sydney Poster Session 3, Wed, Dec 9, 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.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026beihang universityPekingInstitute of Software Chinese AcTsinghua University, SEEN-E RoboBeijing University of AeronauticDeep RL

Adaptive Robust Estimator for Policy Optimization in Reinforcement Learning

Zhongyi Li, Wan Tian, Jingyu Chen, Kangyao Huang and 7 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 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
NeurIPS 2026HunanCentral SouthDeep RL

$R^2E$: A Role-driven Reward Evolutionary Framework for Automated Reward Function Design

Shouhao Chang, Xuan Liu, Hongye Zhu, Xinning Chen and 1 more

Sydney Poster Session 6, Thu, Dec 10, 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
NeurIPS 2026Pennsylvania StateMITDeep RL

A Constrained Bi-level Optimization Framework for Constrained Preference-Based Reinforcement Learning

Yue Mao, Siyuan Xu, Shicheng Liu, Minghui Zhu

Atlanta Poster Session 2, Wed, Dec 9, 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.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026The Hong Kong University of ScieHong Kong University of Science Deep RL

DiversePlace: Diversity-Seeking Curriculum Reinforcement Learning for Macro Placement

Wenrui Zhou, Jiashun Liu, Wenji Fang, Zhiyao Xie and 1 more

Sydney Poster Session 2, Tue, Dec 8, 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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026OpenAIU OxfordIndependentDeep RL

Mitigating Reward Hacking via Task Representations

Lillian Sun, Joe Benton, Eric Easley

Sydney Poster Session 1, Tue, Dec 8, 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.

AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026AalborgU Roma "La Sapienza"Deep RL

RL-Guided Contraction of Symbolic Tensor Networks for Quantum Circuit Equivalence

Suhaib Al-Rousan, Christian Schilling, Max Tschaikowski, Kim Larsen

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · 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
NeurIPS 2026Georgia Institute of TechnologyNorthumbriaDeep RL

EpiPivot: Learning to Control the Simplex Method under Epistemic Uncertainty

Guantao Zhao, Mahdi Noorizadegan, Shihao Yang, Nicoleta Serban

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.

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 2026U BristolCardiffU MacauBristol Robotics Laboratory, UniDeep RL

Learning to Search, Searching to Learn: A Closed-Loop Framework for Large-Scale Vehicle Routing

Yongji Fu, Yi Zhou, Gaojie Jin, Guanqun Cao

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · 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
NeurIPS 2026SungkyunkwanSung Kyun KwanDeep RL

Control First, Robustness Next: Decoupled Representation Learning for Visual RL Generalization

heo chanyong, Hyelyn Jeong, Jongchan Park, Seungjun Oh and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 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
NeurIPS 2026ExperienceFlow and MilaMcGill University / Mila / DeepMDeep RL

Permanent and Transient Representations for Continual Reinforcement Learning

Nishanth Anand, Doina Precup

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.

Show 20 more papers