Good Papers

Showing Offline RL Show all papers

80%Highly rated
?Highly ratedVote to see the score
ICML 2026WorkshopOffline RL

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

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

Jude Waide, Robert Lieck

Published Oct 1, 2026 · 0 citations

100% Readers1 of 1 upvoted
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
69%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Science and Technology of ChinUniversity Of Science And TechnoDidi ChuxingOffline RL

Robust Offline Reinforcement Learning against Out-of-Distribution Dynamics in Autonomous Driving

Haozhe Liu, Jie Wang, Rui Yang, Chunyang Liu and 1 more

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

– ReadersNo votes yet
3/20 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: 3 of 20 reviewers recommend it
lenient 2/5
medium 1/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Wisconsin-MadisonU Wisconsin -- MadisonOffline RL

Intra-Option Fitted Q-Evaluation: Evaluating Hierarchical Policies from Non-Hierarchical Data

Yunfu Deng, Josiah Hanna

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 2026Georgia Institute of TechnologyGoogle DeepMind & Georgia TeOffline RL

Spectral Representations for Provably Robust Offline Meta-Reinforcement Learning from Bagged Rewards

Yashas Vaidya, Bo Dai

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 2026U WarwickOffline RL

Distributionally-Robust Policy Learning from Observational Data

Debmalya Mandal

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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026NanjingTencent Game AI CenterOffline RL

Conservatism Controllable Compositional Guidance for Offline Safe Reinforcement Learning

Ruiqi Xue, Shenghe Hu, Xin Gao, Jing-Wen Yang

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 2026Middle East TechnicalUniversität InnsbruckBogaziciOffline RL

Effect-Driven Skill Abstractions for Offline Reinforcement Learning

Burcu Kılıç, David Drexel, Emre Ugur, Justus Piater

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
NeurIPS 2026Pennsylvania StateJohns HopkinsGeorgia Institute of TechnologyOffline RL

Budgeted Multi-Source Counterfactual Annotation for Off-Policy Evaluation

Biao Xiang, Ali Eshragh, Yuexing Li, Kai Wang

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
NeurIPS 2026MITOffline RL

PoEM: Predicting New RL Outcomes from Existing Policies

Kimia Hamidieh, Giannis Daras, Antonio Torralba

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 2026Institute of automation, ChineseInstitute of Automation, ChineseU the Chinese Academy of ScienceOffline RL

Offline Inverse Reinforcement Learning with Unified Diffusion Planning

Hongmin Zhao, Jiyuan Yin, Kexi Yan, Qinglai Wei 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 2026Seoul NationalSeoul National UniverstiyOffline RL

Kernel Value Regression in Offline Reinforcement Learning

Jongyeon Lee, Jaehyoung Jeon, Kim Haneol, Myungjoo Kang

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
NeurIPS 2026U the Chinese Academy of ScienceInstitute of Software, Chinese AU Chinese Academy of SciencesChinese Academy of Sciences, InsOffline RL

OGPO: Offline Goal-conditioned Policy Optimization for Recoverable Vision-Language-Action Models

Xule Gao, Xi Wang, Zehua Zang, Rui Wang and 2 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 2026ZhejiangCollege of Computer Science and zhejiang universityBeihangOffline RL

Distribution Corrected Decision Transformer for Offline Reinforcement Learning with Imbalanced Datasets

Chufan Chen, Bohao Tang, Dejiang Chen, zhang chao and 3 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 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Eastern MichiganOffline RL

GCD: Correcting Hidden-State Bias in Off-Policy Agentic RL

Changyuan Chen, Jianyu Xiang, Jiasheng Luo, Ziye 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
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 2026College of Computer Science and Nanjing University of AeronauticU Osaka / RIKEN AIPNanjing University of AeronauticOffline RL

Value-Rectified Distillation for Flow-based Offline Reinforcement Learning

Ke Jiang, Wen Jiang, Yoshinobu Kawahara, Xiaoyang Tan

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
NeurIPS 2026Seoul NationalVector InstituteKoreaOffline RL

MINT: Meeting-time INdicators for Truncation in Multi-Step Off-Policy RL

Seungyub Han, Taehyun Cho, Dohyeong Kim, Kyungjae Lee 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Toyota Technological Institute aU FloridaTTI-ChicagoOffline RL

Compose Your Oracles: Off Policy Improvement with Aggregated Guidance

Jingtian Ji, Xuefeng Liu, Matthew Walter

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 2026Singapore ManagementOffline RL

ExpRFT: Exponential Reward-Weighted Fine-Tuning for Offline RL in Multi-Turn Dialogue

Huy Dao, Lizi Liao

Sydney Poster Session 2, Tue, Dec 8, 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 2/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026KAISTU MichiganKorea Advanced Institute of ScieOffline RL

Offline Constrained Reinforcement Learning under Partial Data Coverage

Seokmin Ko, Ambuj Tewari, Kihyuk Hong

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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026TsinghuaTsinghua University, TsinghuaOffline RL

Riemannian Admissibility Flow for Offline-to-Online Safe Reinforcement Learning

Yuan Chu, Xuewu Ji

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 2026U AlbertaDeepMindGoogle DeepMindUCL, DeepMindOffline RL

Off-policy Learning with Excursion Policies

Jiamin He, Mark Rowland, Daniel (Zhaohan) Guo, Hado van Hasselt 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Universidad de San AndrésOffline RL

CS-DICE: Offline Reinforcement Learning with Coherent Occupancy Regularization

Jeremías Figueiredo Paschmann

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 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 2026UW-MadisonPIT IN Cop.Offline RL

Variational Approach to Optimal IPS Estimator for Multi-logger Off-Policy Evaluation

Joon Suk Huh, Junghoon Seo

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 2026ZhejiangLancasterU CambridgeOffline RL

Trajectory-Consistent Diffusion Policies for Offline Reinforcement Learning

Yichao Fu, Shangde Gao, Zhuoling Li, Wen Wang 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.

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 2026JilinOffline RL

Optimistic Q-value Adaptation for Offline-to-Online Reinforcement Learning

Hao Wu, Shunhao Zhang, Shuai Lü

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

Post-Selection-Safe Pessimistic Utilities for Offline Multi-Objective Reinforcement Learning

Mingxi Hu, Meiling Yu

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 2026The Chinese University of Hong KVideo RebirthCity University of Hong KongHuawei Technologies Ltd.TencentOffline RL

Efficient Off-Policy RL for Video Generation via Forward-Consistent Reward Matching

Hongzheng Yang, Mengyang LIU, Haoxuan Wu, Kun Li and 2 more

Sydney Poster Session 3, Wed, Dec 9, 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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Indian Institute Of Technology (Indian Institute of Technology, Offline RL

Safe Offline Reinforcement Learning using Behavior Regularisation and Latent Feasibility-Guidance

Mahesh Keswani, Parth Bhardwaj, Ankur Kumar, Raunak Pushpak Bhattacharyya

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 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.

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 2026National University of SingaporePekingOffline RL

Iterative Latent Refinement for Value Learning in Offline Goal-Conditioned RL

Daoxin Li, Songcheng Xu, Guozhang Chen

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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Indian Institute of ScienceIndian Institute of ScienceOffline RL

Bridging Safety and Performance in Autonomous Systems using Offline Reinforcement Learning

Mumuksh Tayal, Manan Tayal, Ravi Prakash

Sydney Poster Session 3, Wed, Dec 9, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026UNISTUlsan National Institute of ScieUlsan National Institute of ScieOffline RL

Escaping Path Mirages in Offline Goal-Conditioned Reinforcement Learning

Seungyul Han, Junhyeon Bae, Jaebak Hwang, Gwanwoo Choi and 1 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
NeurIPS 2026MITMIT Lincoln Laboratory, MassachuBoston University, BostonMassachusetts Institute of TechnOffline RL

LASER: Latent Space Adjoint Matching for Support Constrained Entropy Regularized Offline RL

Songyuan Zhang, Oswin So, Eric Yu, Matthew Cleaveland and 2 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026AmazonAmazon RoboticsDukeOffline RL

A$^2$IQL: Adaptive Asymmetric Implicit Q Learning for Automated Warehouse Consolidation

Guangyi Liu, Andrea Angiuli, Mirko Ristivojevic, Joseph W Durham and 2 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
NeurIPS 2026Seoul NationalOffline RL

AEGIS: Almost Surely Safe Offline Reinforcement Learning

Junseo Lee, Hyeokjin Kwon, Songhwai Oh

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
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026EmoryHarvardShanghai Jiao TongOffline RL

Autoregressive Diffusion World Models for Off-Policy Evaluation of LLM Agents

ADWM estimates LLM agent performance offline via a latent diffusion world model that alternates step-by-step with the policy, avoiding online interaction errors.

Kaixuan Liu, GUOJUN XIONG, Weinan Zhang, Shengpu Tang

Atlanta Poster Session 3, Thu, Dec 10, 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 5/5
medium 4/10
strict 0/5
88%Must read
?Must readVote to see the score
NeurIPS 2026Imperial College LondonImperial College London / MilaOffline RL

Aligning Flow Map Policies with Optimal $Q$-Guidance

Flow map policies learn multi-step jumps across flow dynamics for fast action generation, and FMQ adapts them via optimal closed-form Q-guidance to achieve state-of-the-art offline-to-online RL with 21.3% higher success rates.

Christos Ziakas, Alessandra Russo, Joey Bose

Sydney Poster Session 3, Wed, Dec 9, 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.

AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Korea Advanced Institute of ScieKAISTOffline RL

Trust Region Q Adjoint Matching

TRQAM introduces trust-region Q-adjoint matching with adaptive path-space KL control via projected dual descent, enabling stable off-policy flow-policy fine-tuning and achieving 68% success on OGBench.

Yonghoon Dong, Kyungmin Lee, Changyeon Kim, Jaehyuk Kim and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 24 on Hugging Face · Code ★ 20

– 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 2/5
medium 7/10
strict 2/5
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Illinois Urbana-ChampaignCalifornia Institute of TechnoloU Illinois at Urbana-ChampaignOffline RL

Beyond Pessimism: Offline Learning in KL-regularized Games

A pessimism-free offline algorithm for KL-regularized games achieves O(1/n) sample complexity via equilibrium stability and smooth best responses.

Yuheng Zhang, Claire Chen, Nan Jiang

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 2/5
medium 6/10
strict 3/5
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Illinois at Urbana-ChampaignOffline RL

Q-MMR: Off-Policy Evaluation via Recursive Reweighting and Moment Matching

Q-MMR evaluates off-policy returns via recursive moment-matching weights learned inductively, guaranteeing dimension-free finite-sample error under Q-realizability alone.

Nan Jiang, Xiang Li

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 2/5
medium 4/10
strict 3/5
Show 20 more papers