Reinforcement Learning

Also known as RL

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

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Imitation Learning for Elder-Facing Speech Synthesis
Jun 19, 2026Dongrui Han, Weidong Chen, Jiawen Kang +3Reinforcement Learning TTS Synthesis
The Chinese University of Hong Kong, Hong Kong SAR, China · Tencent Hunyuan, China
When Do Intrinsic Rewards Work for Code Reasoning? A Comprehensive Study
Jun 18, 2026Xiaolong Jin, Xuandong Zhao, Wenbo Guo +2RL for Code Generation Intrinsic Reward Methods
Purdue University · UC Berkeley · UC Santa Barbara
Evolutionary Discovery of Developmental Reward Schedules in Deep Reinforcement Learning
Jun 18, 2026Alan Nadelsticher RuvalcabaReinforcement Learning Sparse-Reward RL
College of Computing at the Georgia Institute of Technology, Georgia, USA · School of Engineering and Applied Science at the University of Pennsylvania, Pennsylvania, USA
ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems
Jun 18, 2026Veronica Saz Ulibarrena, Simon Portegies ZwartReinforcement Learning Scientific ML
Leiden Observatory, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
CRAX: Fast Safe Reinforcement Learning Benchmarking
Jun 18, 2026Tristan Tomilin, Mourad Boustani, Mickey Beurskens +2RL Benchmarks Reinforcement Learning
Eindhoven University of Technology
A Model-Driven Approach for Developing Families of Reinforcement Learning Environments
Jun 18, 2026Xiaoran Liu, Istvan DavidSoftware Engineering Reinforcement Learning
McMaster University · Hamilton, Canada
ELVA: Exploring Ranking-Driven Universal Multimodal Retrieval
Jun 18, 2026Yuhan Liu, Pei Fu, Hang Li +8Reinforcement Learning Multimodal Large Language Models
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University · MiLM Plus, Xiaomi Inc · Zhongguancun Academy, Beijing, China
A Multi-Agent system for Multi-Objective constrained optimization
Jun 18, 2026Federica FilippiniMulti-Objective Reinforcement Learning Multi-Agent System Optimization
University of Milano-Bicocca Milan, Italy
Augmenting Game AI with Deep Reinforcement Learning
Jun 18, 2026Alessandro Sestini, Joakim Bergdahl, Amir Baghi +3Reinforcement Learning Game-Playing Agents
Electronic Arts (EA), Stockholm, Sweden
Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
Jun 18, 2026Ziheng Wei, Annie Qu, Rui MiaoReinforcement Learning Off-Policy Evaluation
Department of Statistics, University of Michigan at Ann Arbor · Department of Statistics and Applied Probability, University of California at Santa Barbara · Department of Mathematical Sciences, University of Texas at Dallas
Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning
Jun 18, 2026Asaf Cassel, Aviv RosenbergRegret Minimization in RL Reinforcement Learning
Google Research
Process-Verified Reinforcement Learning for Theorem Proving via Lean
Jun 18, 2026Minsu Kim, Se-Young YunReinforcement Learning Automated Theorem Proving
KAIST AI
MetaResearcher: Scaling Deep Research via Self-Reflective Reinforcement Learning in Adversarial Virtual Environments
Jun 18, 2026Wei Yu, Suxing Liu, Minjie Yu +4Reinforcement Learning Deep Research Agents
School of Digital Arts, Jiangxi Arts & Ceramics Technology Institute, Jingdezhen 33001, China · Universiti Sains Malaysia, 11800 USM Penang, Malaysia
Beyond Entropy: Learning from Token-Level Distributional Deviations for LLM Reasoning
Jun 18, 2026Xuanzhi Feng, Zhengyang Li, Zeyu Liu +6Reinforcement Learning RL for Language Model Reasoning
The Hong Kong University of Science and Technology, Hong Kong, China · Sichuan University, Chengdu, China · The Hong Kong Polytechnic University, Hong Kong, China
OnDeFog: Online Decision Transformer under Frame Dropping
Jun 18, 2026Daiki Yotsufuji, Kenta Nishihara, Shoma Shimizu +2Reinforcement Learning Transformer
Yokohama National University, Kanagawa, Japan
Multi-Granular Attention-Driven Reinforcement Learning Framework for Web Intelligent Enhancement Systems
Jun 18, 2026Navin Chhibber, Deepak Singh, Anokh Kishore +2Reinforcement Learning Multi-Agent Reinforcement Learning
Infinity Tech Group Sunnyvale, CA, USA · Gainwell Technologies USA · Capital One USA +2
Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training
Jun 17, 2026Jianzhe LinRL for Code Generation Reinforcement Learning
MetaAI · *Work done at Meta
The Reward Was in Your Data All Along: Correcting Flow Matching with Discriminator-Guided RL
Jun 17, 2026Nicolas Beltran-Velez, Felix Friedrich, Zhang Xiaofeng +4Flow Matching Reinforcement Learning
FAIR at Meta · Columbia University · Mila – Québec AI Institute +3
Pareto Q-Learning with Reward Machines
Jun 17, 2026Arnaud Lequen, Clément Legrand-Lixon, Léo SaulièresMulti-Objective Reinforcement Learning Reinforcement Learning
Linköping University, Sweden · Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRIStal, F-59000 Lille, France · Univ. Toulouse, INRAE-MIAT, Toulouse, France
EfficientRollout: System-Aware Self-Speculative Decoding for RL Rollouts
Jun 17, 2026Minseo Kim, Minjae Lee, Seunghyuk Oh +7RL for Language Models Reinforcement Learning
FuriosaAI · University of California, Berkeley
Online Reward-Punishment Learning from Fixed-Channel Perceptual Event Streams without Environment Rewards
Jun 17, 2026Zirong LiReward Modeling Reinforcement Learning
Tiangong University
Be Your Own Teacher: Steering Protein Language Models via Unsupervised Reward Optimization
Jun 17, 2026Lanqing Li, Shentong Mo, Yang Yu +1RL for Language Models Reinforcement Learning
The Chinese University of Hong Kong · MBZUAI · Hong Kong University of Science and Technology
GraphPO: Graph-based Policy Optimization for Reasoning Models
Jun 17, 2026Yuliang Zhan, Xinyu Tang, Jian Li +7Reinforcement Learning LLM Reasoning with Graphs
Gaoling School of Artificial Intelligence, Renmin University of China · Ant Group
Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement
Jun 17, 2026Kinam Kim, Namiko Saito, Heecheol Kim +3Reinforcement Learning Zero-Shot Robotic Manipulation
KAIST, South Korea · Microsoft Research Asia - Tokyo, Japan · The University of Tokyo, Japan
Reinforcement Learning Foundation Models Should Already Be A Thing
Jun 17, 2026Abdelrahman Zighem, Jill-Jênn VieSynthetic Data Pretraining Reinforcement Learning
Ecole normale supérieure de Paris, PSL University, Paris, France · Soda team, Inria Saclay, Palaiseau, France.
Benchmarking Action Spaces in Reinforcement Learning for Vision-based Robotic Manipulation
Jun 17, 2026Seyed Alireza Azimi, Homayoon Farrahi, Abhishek Naik +2RL for Robotics Reinforcement Learning
Department of Computing Science, University of Alberta · National Research Council Canada · School of Electrical Engineering and Computer Science, University of Ottawa +3
Do as the Romans Do: Learning Universal Behaviors from Heterogeneous Agents
Jun 16, 2026Caleb Chang, Davin Win Kyi, Natasha Jaques +1Reinforcement Learning Imitation Learning
University of Washington · NVIDIA
Learning-Based Decision Making for Combustion Phasing Control in Multi-Fuel CI Engines with Latent Fuel Reactivity Estimation
Jun 16, 2026Rajasree Sarkar, Aditya Satish Patil, Arunava Banerjee +4Reinforcement Learning Partially Observable RL
Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA. · DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD, USA, 21005.
LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents
Jun 16, 2026Haoyang Fang, Wei Zhu, Boran Han +11Reinforcement Learning Large Language Model-Guided Optimization
†LLMZero Project Core Team. · ∗Work done at Amazon.
Deep Reinforcement Learning for Minimum Zero-Forcing Sets
Jun 16, 2026Steve Halley, Maurício GruppiReinforcement Learning Combinatorial Optimization
Department of Computing Sciences, Villanova University Villanova, Pennsylvania, USA

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Imitation Learning for Elder-Facing Speech Synthesis

Dongrui Han, Weidong Chen, Jiawen Kang, Mingyu Cui+2

The Chinese University of Hong Kong, Hong Kong SAR, China · Tencent Hunyuan, China

Reinforcement Learning TTS Synthesis Group Relative Policy Optimization Imitation Learning

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Recent advances in text-to-speech (TTS) synthesis have achieved highly natural and expressive speech generation. However, these systems are designed for general adults and overlook older adults' speech comprehension needs due to age-related sensory and cognitive decline. Prior work involves older adults by collecting preference feedback to tune model parameters. However, obtaining sufficient preference data is costly and difficult, as older adults quickly become fatigued during collection. In this paper, we propose a novel imitation learning (IL) framework to learn TTS models from expert demonstrations. We further improve Group Relative Policy Optimization (GRPO) with two-stage on-policy reward learning (OPRL) to mitigate reward hacking under limited supervision from expert demonstration. Experimental results show that GRPO w/ OPRL outperforms GRPO and supervised baselines in objective and subjective metrics. Audio samples are available at https://dongru1.github.io/demo/im-efss

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Latest papers 1,138