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arXivDeep RL

MEND: RL For Flow Models via Proximal Velocity Matching

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

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

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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NeurIPS 2026Australian NationalDeep RL

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

Jingyang You, Hanna Kurniawati

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

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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

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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

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NeurIPS 2026Massachusetts Institute of TechnHarvardDeep RL

Hindsight Relabeling is All You Need for Reach-Avoid Learning

Kevin Li, Marinka Zitnik

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

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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

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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

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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

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