Rubric-Based RL

RL: Reinforcement Learning

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19 papers in the last four weeks, up 58% on the four weeks before. 0.2% of all new papers.

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ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering
Aug 11, 2026Taojie Zhu, Yuan Xia, Tao Sun +8Rubric-Based RL Medical QA
Tsinghua University · Ant Group · Zhejiang University
RISE-RL: Rubric-Informed Selective Exploration for Open-Ended Reinforcement Learning
Aug 10, 2026Jinkun Hou, Zhuo Liu, Huimin Ren +3Open-Ended Generation RL for Language Models
1Peking University · 2Beijing Institute of Technology · 3Li Auto Inc.
Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning
Aug 3, 2026Fangxu Yu, Tao Feng, Dehai Min +6Audio Reasoning Rubric-Based RL
University of Maryland, College Park · University of Illinois Urbana-Champaign · University of Illinois Chicago +2
SERPO: Self-Evolving Rubric Policy Optimization for Open-Ended Test-Time Reinforcement Learning
Jul 29, 2026Jianze Wang, Kunwang Zheng, Ying Liu +5Reinforcement Learning Test-Time RL
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · Alibaba Group · University of Science and Technology of China
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization
Jul 28, 2026Bo-Wen Zhang, Junwei He, Wen Wang +5Token-Level Credit Assignment Rubric-Based RL
State Key Laboratory of Novel Software Technology, Nanjing University · School of Intelligence Science and Technology, Nanjing University · ByteDance +1
Co-Evolving LLM Evaluators and Policies via DynamicRubric
Jul 22, 2026Beining Wang, Weihang Su, Hongtao Tian +8RL for Language Models LLM Evaluation
Department of Computer Science and Technology, Tsinghua University · 2WeChat, Tencent
Rewarding Better Thinking for LLM Preference Alignment
Jul 22, 2026Xubo Liu, Wenya Guo, Ruxue Yan +2Process Reward Models Credit Assignment in RL
VCIP, DISSec, College of Computer Science, Nankai University, Tianjin, China
Beyond Score Prediction: LLM-Based Essay Scoring and Feedback Generation via Reinforcement Learning with Rubric Rewards
Jul 21, 2026Xuefeng Jin, Jiashuo Zhang, Teng Cao +1Automated Essay Scoring Rubric-Based RL
Alibaba Cloud Computing, Alibaba Group
LLM-as-a-Coach: Experiential Learning for Non-Verifiable Tasks
Jul 20, 2026Tianzhu Ye, Li Dong, Guanheng Chen +4Reinforcement Learning Rubric-Based RL
Microsoft Research · Tsinghua University · Peking University
CriPO: Enhancing Rubric-based RL via Self-Distillation
Jul 20, 2026Mingxuan Xia, Yuhang Yang, Chao Ye +7Credit Assignment in RL Rubric-Based RL
Zhejiang University · ByteDance
Claim-Level Rubric Rewards for Video Caption Reinforcement Learning
Jul 6, 2026Mingqi Gao, Hongyuan Dong, Yifei Chen +6Reward Modeling Video Captioning
1Tsinghua Shenzhen International Graduate School, Tsinghua University · 3LLM Department, Tencent · University of Chinese Academy of Sciences
LLM-as-a-Tutor: Policy-Aware Prompt Adaptation for Non-Verifiable RL
Jul 5, 2026Yujin Kim, Namgyu Ho, Sangmin Hwang +7RL for Language Models Reinforcement Learning
1KAIST · 2Upstage · University of Toronto +2
EvoRubrics: Dynamic Rubrics as Rewards via Adversarial Co-Evolution for LLM Reinforcement Learning
Jun 22, 2026Hongxin Ding, Baixiang Huang, Yue Fang +6RL for Language Models Rubric-Based RL
National Engineering Research Center of Software Engineering, Peking University, China · School of Computer Science, Peking University, Beijing, China · Key Laboratory of High Confidence Software Technologies, Ministry of Education +2
ARCO: Adaptive Rubric with Co-Evolution for Multi-Step LLM-Based Agents
Jun 19, 2026Zihang Tian, Jingsen Zhang, Rui Li +3Process Reward Models Credit Assignment in RL
Renmin University of China
DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents
Jun 15, 2026Minghang Zhu, Chuyang Wei, Junhao Xu +3Deep Research Agents Rubric-Based RL
Shandong University, Qingdao, China · Zhongguancun Academy, Beijing, China · Fudan University, Shanghai, China
ExpRL: Exploratory RL for LLM Mid-Training
Jun 15, 2026Violet Xiang, Amrith Setlur, Chase Blagden +2Reinforcement Learning RL for Language Model Reasoning
1Stanford University · 2Carnegie Mellon University · 3OpenAI +1
Rubric-Guided Self-Distillation: Post-Training Without Rubric Verifiers
Jun 10, 2026MohammadHossein Rezaei, Anas Mahmoud, Zihao Wang +6Rubric-Based RL Language Model Distillation
Scale AI
ComplexConstraints and Beyond: Expert Rubrics for RLVR
Jun 8, 2026Sushant Mehta, Liudas Panavas, Suhaas Garre +1LLM-as-a-Judge Rubric-Based RL
Surge AI
Reproducing, Analyzing, and Detecting Reward Hacking in Rubric-Based Reinforcement Learning
Jun 3, 2026Xuekang Wang, Zhuoyuan Hao, Shuo Hou +3Reward Hacking RL for Language Models
Tsinghua University · Harbin Institute of Technology, Shenzhen · Xi’an Jiaotong University
QUBRIC: Co-Designing Queries and Rubrics for RL Beyond Verifiable Rewards
Jun 2, 2026Rongzhi Zhang, Rui Feng, Zhihan Zhang +8Reinforcement Learning RL for Language Model Reasoning
Amazon · Georgia Institute of Technology
Mitigating False Credit Propagation: Probabilistic Graphical Reward Aggregation for Rubric-Based Reinforcement Learning
Jun 2, 2026Can Lv, Mingju Chen, Heng Chang +1Reward Modeling RL for Language Models
Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, School of Artificial Intelligence, Beihang University · Tsinghua University
RUBAS: Rubric-Based Reinforcement Learning for Agent Safety
Jun 2, 2026Xian Qi Loye, Qinglin Su, Zhexin Zhang +5Reinforcement Learning AI Agent Safety
The Conversational AI (CoAI) group, DCST, Tsinghua University · Huawei Noah’s Ark Lab
ARBOR: Online Process Rewards via a Reusable Rubric Buffer for Search Agents
Jun 2, 2026Zheng Liu, Longxiang Zhang, Xintong Wang +8Reward Modeling Process Reward Models
Tsinghua University · Alibaba Group · Peking University +1
Deep Research as Rubric for Reinforcement Learning
May 31, 2026Wangyi Mei, Zhouhong Gu, Zhenhan Bai +9Open-Ended Generation Reinforcement Learning
Fudan University · Xiaohongshu Inc. · Beijing University of Posts and Telecommunications
Reinforcement Learning with Robust Rubric Rewards
May 28, 2026Ya-Qi Yu, Hao Wang, Fangyu Hong +15Reinforcement Learning Rubric-Based RL
Huawei Technologies Co., Ltd.
EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation
May 28, 2026Xin Guan, Xiaomeng Hu, Shen Huang +6Open-Ended Generation RL for Language Models
Tongyi Lab, Alibaba Group
Prompt-Level Reward Specifications for Open-Ended Post-Training
May 28, 2026Zijun Weng, Xiaohui Hu, Shuangyong Song +3Open-Ended Generation Reward Modeling
1Fudan University · 2Xingchen AGI Lab, China Telecom Artificial Intelligence Technology (Beijing) Co., Ltd.
Tournament-GRPO: Group-Wise Tournament Rewards for Reinforcement Learning in Open-Ended Long-Form Generation
May 26, 2026Zixuan Yang, Yiqun Chen, Wei Yang +7Open-Ended Generation Reward Modeling
Renmin University of China · University of Southern California · Zhejiang University +1
Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
May 26, 2026Yu Huang, Zihua Zhao, Zhaoxin Huan +9Multi-Objective Reinforcement Learning RL for Language Models
Shanghai Jiao Tong University · Ant Group
ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning
May 22, 2026Xiaoyuan Li, Keqin Bao, Moxin Li +5RL for Language Models Reinforcement Learning
University of Science and Technology of China · Alibaba Group · National University of Singapore

Aug 11, 2026, cs.CLJ/K move · Enter open · S save

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

Taojie Zhu, Yuan Xia, Tao Sun, Yizhi Wang+7

Tsinghua University · Ant Group · Zhejiang University

Rubric-Based RL Medical QA Reinforcement Learning with Verifiable Rewards Rubric-Guided Generation

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Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many open-ended medical questions lack comparably cheap outcome verifiers: responses may be partly correct, incomplete, or contain clinically consequential errors. Rubrics written or validated by physicians offer strong clinical grounding, but involving experts in every instance is costly. Model-generated rubrics make this supervision scalable. We introduce ConRub-Med to preserve useful distinctions as rubric feedback moves from construction to policy optimization. For each prompt, three heterogeneous language models propose atomic criteria independently; a separate model reviews them, retaining only criteria with semantic support from all three generators. Three-State scoring distinguishes correct coverage, missing information, and incorrect claims. Errors receive negative rather than zero credit. When every response in a complete Group Relative Policy Optimization (GRPO) group receives the same final reward, a pairwise judge provides sequence advantages only if both candidate orders agree, without changing the scalar rewards. Groups without ties use vanilla GRPO. In a blinded study matched by question, two medical experts rate panels from the full pipeline as more clinically relevant than panels produced by one generator. Across the evaluated open models, ConRub-Med ranks first on six of nine benchmarks and achieves the highest medical and generalization averages. Using the resulting rubric dataset of 5,166 prompts, it scores

38.98 \pm 1.04

(mean

\pm

SD) on HealthBench-Hard, compared with InfiMed-ORBIT's 33.60 with 8,000 samples and 37.30 with 28,000.

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Latest papers 68