Reinforcement Learning

Also known as RL

Follow this topic Ask about this topic

Momentum

144 papers in the last four weeks, up 243% on the four weeks before. 1.4% of all new papers.

Jul 13Week of Sep 28

Latest papers 1,147

All topics

Learning to Compress Time-to-Control: A Reinforcement Learning Framework for Chronic Disease Management
May 10, 2026Prabhjot Singh, Abhishek Gupta, Chris Betz +4Reinforcement Learning Type 1 Diabetes
Altitude
ConFit v3: Improving Resume-Job Matching with LLM-based Re-Ranking
May 10, 2026Xiao Yu, Ruize Xu, Chengyuan Xue +6Reinforcement Learning Learning to Rank
Columbia University · New York, NY, USA · John Hopkins University +6
One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
May 10, 2026Bowen He, Juncheng Dong, Lin Lin +1Reinforcement Learning Transformer
Duke University, Durham, U.S.A.
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
May 10, 2026Anish Diwan, Davide Tateo, Christopher E. Mower +3Reinforcement Learning Policy Optimization
Technical University of Darmstadt · Robotics Institute Germany (RIG) · Lund University +3
ACSAC: Adaptive Chunk Size Actor-Critic with Causal Transformer Q-Network
May 10, 2026Qian Chen, Junqiao Zhao, Hongtu Zhou +4Reinforcement Learning Transformer-Based RL
Tongji University
From Passive Reuse to Active Reasoning: Grounding Large Language Models for Neuro-Symbolic Experience Replay
May 10, 2026Yanan Xiao, Yixiang Tang, Zechen Feng +3Reinforcement Learning Experience Replay
1Affiliation 1 · 2Affiliation 2 · 3Affiliation 3
Functional Graphs for Predicting and Explaining Goal Failure in Sparse Goal-Conditioned RL
May 10, 2026Shalley DashReinforcement Learning Sparse-Reward RL
Associate Adjunct Professor, Business Analytics, Institute of Management Technology Ghaziabad, 201001
PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning
May 10, 2026Dongyi Liu, Yifan Niu, Qinwen Wang +2Reinforcement Learning Reward Shaping
The Hong Kong University of Science and Technology (Guangzhou) · The Hong Kong University of Science and Technology
Learning the Preferences of a Learning Agent
May 9, 2026Karim Abdel Sadek, Mark Bedaywi, Rhys Gould +1Reinforcement Learning Preference Learning
University of California, Berkeley
DARE: Difficulty-Adaptive Reinforcement Learning with Co-Evolved Difficulty Estimation
May 9, 2026Yang Zhou, Can Jin, Zihan Dong +7Reinforcement Learning RL for Language Model Reasoning
Rutgers University · Amazon · Washington University +1
Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs
May 9, 2026Xiaozhe Li, Xinyu Fang, Shengyuan Ding +5RL Benchmarks Reinforcement Learning
Tongji University1 · Shanghai AI Lab2 · Zhejiang University3 +3
BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning
May 9, 2026Yuhang Xu, Kaibin Tian, Yang Tian +6Reinforcement Learning Speculative Decoding
1Shanghai Jiao Tong University · 2Bytedance
Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents
May 9, 2026Minzheng Wang, Run Luo, Yanbo Wang +6Reinforcement Learning Self-Play RL
MAIS, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · National University of Singapore +1
The Cancellation Hypothesis in Critic-Free RL: From Outcome Rewards to Token Credits
May 9, 2026Tianhao Cheng, Zeyu Huang, Zihan Qiu +5Reinforcement Learning Token-Level Credit Assignment
1Fudan University · 3The University of Edinburgh · 6Qwen Team, Alibaba Group +4
MARLaaS: Multi-Tenant Asynchronous Reinforcement Learning as a Service
May 8, 2026Timothy Tin Long Yu, Gursimran Singh, Ge Shi +3Asynchronous RL Reinforcement Learning
Huawei Technologies Canada
DUET: Optimize Token-Budget Allocation for Reinforcement Learning with Verifiable Rewards
May 8, 2026Haoyu Hu, Xuandong Zhao, Xuhai "Orson'' Xu +1Reinforcement Learning Group Relative Policy Optimization
Cornell University · University of California, Berkeley · Columbia University
Rubric-Grounded RL: Structured Judge Rewards for Generalizable Reasoning
May 8, 2026Manish Bhattarai, Ismael Boureima, Nishath Rajiv Ranasinghe +2Reinforcement Learning RL for Language Model Reasoning
Los Alamos National Laboratory, Los Alamos, NM, USA.
Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
May 8, 2026Gugan Thoppe, L. A. Prashanth, Ankur Naskar +1Markov Decision Processes Reinforcement Learning
Computer Science and Automation, Indian Institute of Science, Bengaluru · Computer Science and Engineering, Indian Institute of Technology Madras, Chennai · Tata Consultancy Services Limited, Hyderabad
Interpreting Reinforcement Learning Agents with Susceptibilities
May 8, 2026Chris Elliott, Einar Urdshals, David Quarel +1Reinforcement Learning Neural Network Interpretability
Timaeus
Actor-Critic Algorithm for Dynamic Expectile and CVaR
May 8, 2026Yudong Luo, Erick DelageReinforcement Learning Risk-Sensitive RL
1GERAD & Department of Decision Sciences, HEC Montr´eal, Canada · 2Mila - Quebec AI Institute, Canada
Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works
May 8, 2026Wenhua Nie, Jianan Wu, Junlin Liu +6Reinforcement Learning Group Relative Policy Optimization
National Taiwan University
SEIF: Self-Evolving Reinforcement Learning for Instruction Following
May 8, 2026Qingyu Ren, Qianyu He, Jiajie Zhu +7RL for Language Models Reinforcement Learning
Shanghai Key Laboratory of Data Science, College of Computer Science and Artificial Intelligence, Fudan University · School of Data Science, Fudan University · Ant Group
RELO: Reinforcement Learning to Localize for Visual Object Tracking
May 8, 2026Xin Chen, Chuanyu Sun, Jiao Xu +4Reinforcement Learning Visual Object Tracking
City University of Hong Kong · Dalian University of Technology · Hunyuan Team, Tencent
Beyond Linear Attention: Softmax Transformers Implement In-Context Reinforcement Learning
May 8, 2026Zixuan Xie, Xinyu Liu, Claire Chen +3Reinforcement Learning Transformer-Based RL
University of Virginia · California Institute of Technology · Purdue University
SparseRL-Sync: Lossless Weight Synchronization with ~100x Less Communication
May 8, 2026Lucas Hu, Ranchi Zhao, Isaac Zhu +4Reinforcement Learning Communication-Efficient Distributed Training
Scitix
Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models
May 8, 2026Xiaoze Liu, Dhananjay Ram, Yuting Zhang +3RL for Language Models Reinforcement Learning
1Purdue University · *Work done during an internship at Amazon. · 2AWS Agentic AI
Improved Model-based Reinforcement Learning with Smooth Kernels
May 8, 2026Kun Long, Yuqiang Li, Xianyi WuReinforcement Learning Continuous-Time RL
School of Statistics, KLATASDS-MOE, East China Normal University, North Zhongshan Road, Shanghai, 200062, PR China.
Adaptive Negative Reinforcement for LLM Reasoning:Dynamically Balancing Correction and Diversity in RLVR
May 8, 2026Yash Ingle, Jaival Chauhan, Ankit Yadav +1Reinforcement Learning RL for Language Model Reasoning
Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India
Convergence and Emergence of In-Context Reinforcement Learning with Chain of Thought
May 8, 2026Zixuan Xie, Xinyu Liu, Rohan Chandra +1Reinforcement Learning Transformer
University of Virginia
Almost Sure Convergence Rates of Stochastic Approximation and Reinforcement Learning via a Poisson-Moreau Drift
May 8, 2026Xinyu Liu, Zixuan Xie, Shangtong ZhangReinforcement Learning Stochastic Approximation
University of Virginia

May 10, 2026, cs.LGJ/K move · Enter open · S save

Learning to Compress Time-to-Control: A Reinforcement Learning Framework for Chronic Disease Management

Prabhjot Singh, Abhishek Gupta, Chris Betz, Abe Flansburg+3

Altitude

Reinforcement Learning Type 1 Diabetes Healthcare Offline RL

Open paper AskPDF arXiv

Reinforcement learning (RL) in healthcare has had mixed results, with reward sparsity, unreliable off-policy evaluation, and deployment-simulation gap as recurring failure modes. We argue that chronic disease management is structurally a more tractable RL setting than the acute-care problems the field has primarily studied, but only if the problem is formalized to exploit chronic care's properties. We propose such a formalization. The agent's objective is to compress time-to-control (TTC) under a tiered reward calibrated to the CMS ACCESS Model. Two quantities from our companion preference-learning paper [Singh et al. 2026] enter as load-bearing structural elements: the execution intensity εbounds action availability under a constrained Markov Decision Process, and the clinician capability κweights offline-data transitions during RL training. Together they couple preference learning and RL into a two-loop architecture. We present simulation results on synthetic state machines for hypertension and type 2 diabetes. Capability-weighted offline RL outperforms uniform-weighted offline RL and the behavior policy by 15 percentage points on T2D TTC; the uniform-weighted formulation (the standard in existing healthcare RL) underperforms even the heterogeneous behavior policy. \Epsilon-aware policies generalize across deployment regimes while ε-naive policies do not.

Momentum

Related topics

Latest papers 1,147