RL for Language Model Reasoning

RL: Reinforcement Learning

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91 papers in the last four weeks, up 176% on the four weeks before. 0.9% of all new papers.

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From Rollouts to Recipes: Self-Contained Post-Training for LLMs
Sep 1, 2026Yifei Li, Lingling Zhang, Muye Huang +3Self-Training for Language Models RL for Language Model Reasoning
School of Computer Science and Technology, Xi’an Jiaotong University, China · Shaanxi Province Key Laboratory of Big Data Knowledge Engineering · Zhongguancun Academy, Beijing, China +1
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
CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN
Sep 1, 2026Pranshav Gajjar, Vijay K Shah6G Networks LLM Interpretability
NextG Wireless Lab NCSU Raleigh USA
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
MedAgent-R1: Faithfulness-Aware Reinforcement Learning for Evidence-Grounded Medical Reasoning
Aug 31, 2026Jiangwang Chen, Chenghao Zhang, Hengxing CaiLLM Hallucination Mitigation Evidence-Grounded Reasoning
Tsinghua University · DP Technology
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
PAC: Progress-Augmented Advantage Curriculum for Multi-Task Reinforcement Learning of LLMs
Aug 31, 2026Yuanqiang Yu, Yanzhao Zheng, Zhentao Zhang +8RL for Language Model Reasoning Curriculum RL
Alibaba Group, Hangzhou, China
Learning Where Outcomes Change:Credit-Addressable Reasoning for Multimodal Geometry
Aug 31, 2026Jiani Guo, Junjie Wang, Jie Wu +5RL for Language Model Reasoning Credit Assignment in RL
1Tsinghua University · 3Zhejiang University · 2Microsoft Research
COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning
Aug 31, 2026Shrinidhi Kumbhar Santosh Mashetty Divij Handa Kevin Coutinho, Siddharth Sambhaji Ghule, Chitta BaralRL for Language Model Reasoning LLM Post-Training
Arizona State University
Beyond Uncertainty: Multi-Solver Disagreement Rewards for Self-Evolving Reasoning Curricula
Aug 30, 2026Vinoth Selvendran, Zhanming ZhangReward Modeling RL for Language Model Reasoning
Independent Researcher · Palo Alto, CA, USA · New York, NY, USA
ManGo: Manga Active Narrative Grounding Optimization
Aug 30, 2026Hao Qiu, Junyan Wang, Zheyuan Liu +4Visual Question Answering RL for Language Model Reasoning
1Communication University of China · 2Australian Institute for Machine Learning, Adelaide University · University of New South Wales +2
JPO: Juris Policy Optimization for Structured Legal Reasoning in Criminal Judgment Prediction
Aug 30, 2026Zhaolu Kang, Yantao Liu, Tailong Luo +14Legal NLP Legal Judgment Prediction
Hunyuan, Tencent · Peking University · Tsinghua University +5
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
SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning
Aug 27, 2026Zhuochun Li, Yuelyu Ji, Yiming Zeng +1Process Reward Models RL for Language Model Reasoning
University of Pittsburgh, Pittsburgh, USA · University of Connecticut, Storrs, USA
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
Beyond Forgetting: Diagnosing and Harnessing Shared Reasoning in Continual RLVR
Aug 19, 2026Lirui Luo, Guoxi Zhang, Hongming Xu +3RL for Language Model Reasoning Replay-Based Continual Learning
State Key Lab of General AI, School of Intelligence Science and Technology, Peking University · State Key Laboratory of General Artificial Intelligence, BIGAI · Beijing Institute of Technology +1
PertMind: Eliciting Emergent Biological Reasoning in LLM via Reinforcement Learning on Cellular Perturbation Data
Aug 17, 2026Zhenchao Tang, Xiaogang Xu, Jiafei Wu +16RL for Language Model Reasoning Single-Cell Perturbation Modeling
Zhejiang University
Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Aug 17, 2026Yixuan Wang, Yifei Chen, Haichao Zhang +6Multi-Objective Reinforcement Learning RL for Language Model Reasoning
University of Florida · UC San Diego · Northeastern University +3
GCPO: Diagnosing and Constraining Subspace Geometry in Rollout RL for LLMs
Aug 12, 2026Kai Yang, Jingwei Xu, Wanyu Wang +4RL for Language Model Reasoning Constrained RL
School of Computer Science, Shanghai Jiao Tong University · Shanghai Artificial Intelligence Laboratory · NovaCore +3
Reinforcing Step-level Reasoning for Effective Self-Correction in LLMs
Aug 12, 2026Vu Duc Anh, Nhat M. Hoang, Do Xuan Long +3LLM Self-Correction Direct Preference Optimization
Nanyang Technological University, Singapore · National University of Singapore · Institute for Infocomm Research (I2R), A*STAR +1
PAIR: Pairwise-Aware Inclusion Reweighting for Adaptive Rollout Allocation in RLVR
Aug 11, 2026Pixel Nomand, Elena Voss, Marcus Hale +1Inverse Probability Weighting Reinforcement Learning
University of Wisconsin–Madison · University of Washington
Distill Skills into Weights, Not Prompts: Abstract Skills as Privileged Signals for On-Policy Self-Distillation
Aug 10, 2026Yubo Jiang, Fengying Xie, Zhiguo Jiang +1On-Policy Self-Distillation RL for Language Model Reasoning
School of Astronautics, Beihang University, Beijing 102206, China · Longcat Interaction Team, Meituan, Beijing 100102, China · Tianmushan Laboratory, Beihang University, Hangzhou 311115, China
Parameter Exploration for RLVR via Variational Learning
Aug 10, 2026Vatsal Venkatkrishna, Nico Daheim, Iryna GurevychRL for Language Model Reasoning RL Exploration
INSAIT, Sofia University “St. Kliment Ohridski”, Bulgaria · Ubiquitous Knowledge Processing Lab (UKP Lab), Department of Computer Science, Technical University of Darmstadt and National Research Center for Applied Cybersecurity ATHENE, Germany
CoRE: Consensus Rewards via Equilibrium for Test-Time Reinforcement Learning
Aug 10, 2026Ambuj Mehrish, Sebastiano VasconReward Modeling RL for Language Models
CVML Lab Ca’ Foscari University of Venice
SoftmaxGRPO: Learning to Reason using Softmax Advantage Group Estimation
Aug 10, 2026Jefferson Hernandez, Jaywon Koo, Zilin Xiao +2RL for Language Model Reasoning Group Relative Policy Optimization
Rice University
Beyond Solvability: Task Learnability as a Static Prior for LLM RL Post-Training
Aug 10, 2026Ting Zhou, Zhenqing Ling, Daoyuan Chen +4Reinforcement Learning RL for Language Model Reasoning
Sun Yat-Sen University · Alibaba Group
Control-Diverse Reinforcement Fine-Tuning: Decoupling the Shared Control Bottleneck of RL Post-Training
Aug 8, 2026Binwen Tan, Jingchao Wang, Dengzhe Hou +6RL for Language Model Reasoning Multi-Task RL
1Graduate School of Information Sciences, Tohoku University · School of Computer Science, Peking University · 2Unprecedented-scale Data Analytics Center, Tohoku University +3
DASH: Divergence-Adaptive Supervision Horizons for On-Policy Self-Distillation of Reasoning Models
Aug 6, 2026ZhiYan Hou, Xinyu Tang, Hongyan An +9On-Policy Self-Distillation RL for Language Model Reasoning
Institute of Automation, Chinese Academy of Sciences · EverMind · Shanda Group +3
Contextual Information Policy Optimization for Search Agents
Aug 6, 2026Xingyu Guo, Wei Chen, Linlin Yang +1Evidence-Grounded Reasoning RL for Language Model Reasoning
National College for Excellent Engineers, Beihang University, Beijing, China · School of Artificial Intelligence, Beihang University, Beijing, China · State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China
Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning
Aug 5, 2026Yinghui He, Ling Yang, Jiarui Liu +6LLM Evaluation Reasoning Evaluation
Princeton University · Carnegie Mellon University · University of Toronto +3

Sep 1, 2026, cs.CLJ/K move · Enter open · S save

From Rollouts to Recipes: Self-Contained Post-Training for LLMs

Yifei Li, Lingling Zhang, Muye Huang, Zihan Ma+2

School of Computer Science and Technology, Xi’an Jiaotong University, China · Shaanxi Province Key Laboratory of Big Data Knowledge Engineering · Zhongguancun Academy, Beijing, China+1

Self-Training for Language Models RL for Language Model Reasoning LLM Post-Training

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Post-training large language models usually applies a single training recipe to all samples, even though the model's own rollouts reveal different sample-level learning states. We propose Self-Routing, a behavior-conditioned post-training framework that uses rollout correctness and confidence to decide how each sample should be optimized. Depending on its behavior state, a sample is routed to GRPO, on-policy self-distillation, regularization, or skipping, allowing training to adapt without external teachers, extra annotations, or additional sampling. Experiments on mathematical reasoning across Qwen3 and Qwen3.5 backbones show that Self-Routing consistently improves over uniform GRPO, uniform OPSD, fixed mixtures, and simpler routing baselines. Further analyses show that the routing distribution changes over training and reduces unnecessary updates on low-signal or already stable samples.

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