Reinforcement Learning with Verifiable Rewards

Also known as RLVR

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59 papers in the last four weeks, up 119% on the four weeks before. 0.6% of all new papers.

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UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
Sep 17, 2026Wenjie Liao, Liangjie Zhao, Zehong CaoRL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
Waseda University · Adelaide University
Anchoring What Matters: A Dual-Level Learning Framework for Visually-Grounded Multimodal Reasoning
Sep 16, 2026Xinxin Song, Siyuan Li, Tingxiong Xiao +1Credit Assignment in RL Experience Replay
Department of Automation, Tsinghua University · Institute for Brain and Cognitive Science, Tsinghua University
Bellman Policy Optimization
Sep 14, 2026Zhuoqing Song, Haotian Xu, Xikun Zhang +1Reinforcement Learning RL for Language Model Reasoning
1Apodex US, Inc. · 2Princeton University
HISPO: Hierarchical Importance-Sampling Policy Optimization with Entropy-Derived Segments
Sep 14, 2026Quoc-Vinh Lai-Dang, Hyo-Sang ShinRL for Language Model Reasoning Credit Assignment in RL
Cho Chun Shik Graduate School of Mobility KAIST
MInTRL: Off-policy Intervention can boost On-policy RL
Sep 14, 2026Mingyu Chen, Yefan Tao, Gerald Friedland +2Reinforcement Learning Reinforcement Learning with Verifiable Rewards
Amazon Web Services · Boston University
T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks
Sep 12, 2026Junyao Yang, Yucheng Shi, Zhongzhi Li +4Terminal Agents Long-Horizon Agent Evaluation
Tencent Hy Foundation Model · National University of Singapore · University of Georgia +2
Fork Where the Model Changes Its Mind: Belief-Shift Branching for Tree-Structured Reinforcement Learning
Sep 12, 2026Bin Lei, Yu Li, Prafulla Kumar Choubey +7Reinforcement Learning RL for Language Model Reasoning
University of Minnesota · Salesforce AI Research
TRACE: Training Reasoning Agents for Causal Exploration with Synthesized Rewards
Sep 9, 2026Rui Sun, Zhan Shi, Bing HeRL for Language Model Reasoning Causal Reasoning in Language Models
Independent Researchers
Proof-Carrying Cognition: Closing the Verification Gap with Reality-Settled Reward
Sep 9, 2026Eshwar Reddy M, Sourav KarmakarReward Modeling Reward Hacking
AI Engineer, Testsigma University of San Diego · Senior AI Scientist, Intuit India
ThinkPrior: Zero-Rollout Difficulty Priors for Cold-Start Prompt Selection in RLVR
Sep 8, 2026Tommy Sha, Skylar Zhai, Siqi ZhaoRL for Language Model Reasoning Group Relative Policy Optimization
1Stony Brook University · University of Minnesota Twin Cities
Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR
Sep 8, 2026Youngjun Yu, Sanghwan Jang, Hwanjo YuRL for Language Model Reasoning RL Exploration
Pohang University of Science and Technology (POSTECH)
CircuitLens: Reasoning Circuits as Data Selection Signals for Reinforcement Learning with Verifiable Rewards
Sep 7, 2026Zhuofan Chen, Ziqian Jiao, Yikai Cui +3Numerical Reasoning in Language Models Reinforcement Learning
School of Computer Science and Engineering, Beihang University, Beijing, China · Beijing Institute for General Artificial Intelligence, China
VERPO: Verified Evidence Regularized Policy Optimization
Sep 5, 2026Haijiang Li, Chengyu Lv, Yi Zhang +8RL for Language Model Reasoning Credit Assignment in RL
Independent · Tongji University · Fudan University +3
Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR
Sep 3, 2026Boyan Li, Bingsen Chen, Chenghao Yang +3RL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
University of Alberta · New York University · NYU Shanghai +3
Spurious Advantage Hidden in GRPO
Sep 3, 2026Jiamian Wang, Samyadeep Basu, Koustava Goswami +2Reinforcement Learning Group Relative Policy Optimization
Rochester Institute of Technology · Adobe Research
FiMI Banking: A Sovereign Model for Indian Retail Banking
Sep 3, 2026NPCI AI Research Team, Aman Kumar, Asit Desai +15Financial Services RL for Language Models
NPCI AI Research Team
Gradients Know What Outcomes Don't: Unlocking Reinforcement Learning for LLM Reasoning with Gradient-Aligned Rewards
Sep 3, 2026Leqi Zheng, Jinbo Su, Fang Niu +8Numerical Reasoning in Language Models Reward Shaping
Tsinghua University · Renmin University of China · Institute of Information Engineering, CAS +4
DE-Venus: A Data-Efficient RLVR Framework for Large Language Models
Sep 3, 2026Shenzhi Yang, Guangcheng Zhu, Kai Tang +11RL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
1Zhejiang University · 2Ant Group · 3Hong Kong Baptist University +2
FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience
Sep 3, 2026Zixun Huang, Kishan Panaganti, Haitao Mi +1RL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
Tencent HY LLM Frontier · University of Pennsylvania
Cliff: Learning Process Rewards from the First Mistake
Sep 2, 2026Peixuan Han, Runhui Wang, Ketan Ramaneti +3Reinforcement Learning with Verifiable Rewards LLM Reasoning
1Amazon Web Services · University of Illinois Urbana-Champaign
Where the Verifier Fails: A Category-Level Audit of Reward Signals in RLVR
Sep 1, 2026Esther XinLLM Answer Verification Reinforcement Learning with Verifiable Rewards
Independent Researcher
From Base Rollouts to RL Reasoning: A Budgeted Search Perspective
Sep 1, 2026Wenhe Sun, Cunxiang Wang, Zijun Yao +1Inference-Time Search RL for Language Model Reasoning
1Fudan University · 2Zhipu AI · 3Tsinghua University +1
ARISE-RL: Agentic Rubric-Grounded Iterative Self-Evolution with Reinforcement Learning
Sep 1, 2026Fanrui Zhang, Ruixue Ding, Qiang Zhang +13AI Agent Benchmarks Rubric-Based RL
Alibaba ATH Token Foundry · Hema, Alibaba Group
Group Adaptive Clipping Policy Optimization
Aug 31, 2026Sheng Jia, Xiao Wang, Shiva Prasad Kasiviswanathan +1Group Relative Policy Optimization Policy Optimization
University of Toronto · Amazon
Reconciling Process Supervision with Outcome-Based Credit in Agentic Policy Optimization
Aug 31, 2026Jingxiao Yang, Wangjie Gan, Yingxuan Zhuang +3Agentic RL Group Relative Policy Optimization
Zhejiang University
Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence
Aug 31, 2026Zhiqin Yang, Jingwen Fu, Yuhan Liu +16Reinforcement Learning RL for Language Model Reasoning
The Hong Kong University of Science and Technology · Zhongguancun Academy · Xi’an Jiaotong University +6
GMTS: Gradient Magnitude-based Token Selection Improves RLVR Training for LLM Reasoning
Aug 31, 2026Outongyi Lv, Yuanwei Zhang, Xiaoqun ZhangRL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
School of Mathematical Sciences, Shanghai Jiao Tong University · Institute of Natural Sciences, Shanghai Jiao Tong University
ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning
Aug 28, 2026Xin Jiang, Minhao Wang, Wen Wu +4Reward Shaping RL for Language Model Reasoning
School of Computer Science and Technology, East China Normal University, Shanghai 200241, China · State Key Laboratory of Estuarine and Coastal Research, School of Computer Science and Technology, East China Normal University, Shanghai 200241, China
Program Learning with Verifiable Rewards: Symbolic Backpropagation for Post-Training LLMs
Aug 28, 2026Vishvesh BhatLLM-Based Program Synthesis Reinforcement Learning with Verifiable Rewards
CoreThink AI
On-policy Distillation with Verifiable Reward
Aug 25, 2026Wenze Lin, Jiale Zhao, Xitai Jiang +5RL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards
LeapLab, Tsinghua University · Qiuzhen College, Tsinghua University · Beihang University +2

Sep 17, 2026, cs.AIJ/K move · Enter open · S save

UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning

Wenjie Liao, Liangjie Zhao, Zehong Cao

Waseda University · Adelaide University

RL for Language Model Reasoning Reinforcement Learning with Verifiable Rewards Self-Improving Agents Cooperative MARL RL for Tool Use

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Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing methods typically separate trajectory generation from evaluation, relying on static verifiers that cannot adapt to emerging failure modes or self-consistency signals that may reinforce errors shared across trajectories. Jointly adapting planning, execution, and evaluation offers a promising alternative, but introduces a fundamental coordination challenge: each component continuously changes the data or feedback used to train the others. We address this challenge with \textbf{UnifiedPlayers}, a cooperative framework comprising a Planning Player that generates tasks, an Execution Player that produces multi-turn trajectories with Python tool calls, and an Evaluation Player that constructs executable verifiers. We design role-specific rewards that coordinate the three players toward a shared learning objective under GRPO. Across two model backbones and twelve reasoning benchmarks, UnifiedPlayers outperforms the strongest prior baseline by at least 3.5% on mathematical reasoning and 3.9% on general reasoning tasks. Moreover, the learned verifier achieves 84.2% adversarial detection accuracy, while its reward signal exhibits 2.03

\times

higher per-question variance than a self-consistency baseline, providing more discriminative verifications. These results highlight cooperation among specialized players as a promising path toward self-enhanced tool-integrated agents.

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Latest papers 438