RL for VLMs

RL: Reinforcement Learning · VLM: Vision-Language Model

This field studies how reinforcement learning can improve models that interpret images or video alongside language, and sometimes take actions in visual environments. Common approaches include group-relative policy optimization, PPO, and reinforcement learning from verifiable rewards, with feedback based on answer correctness, visual evidence, intermediate reasoning, preferences, or tool use. Applications range from image and video question answering, spatial reasoning, and medical analysis to navigation and robotic manipulation. A central challenge is ensuring that better scores reflect genuine use of visual evidence rather than language shortcuts, while designing reliable rewards and efficient training that generalize beyond the training setting.

Latest papers

476 papers68 papers in the last four weeks, up 94% on the four weeks before. 0.4% of all new papers.

RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning
Feb 25, 2026Yukun Chen, Jiaming Li, Longze Chen +10VLM Reasoning Rubric-Based RL
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Alibaba Group +1
NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning
Feb 24, 2026Ishaan Rawal, Shubh Gupta, Yihan Hu +1Vision-Language-Action Models Autonomous Driving
Applied Intuition · Texas A&M University · UC Berkeley
PyVision-RL: Forging Open Agentic Vision Models via RL
Feb 24, 2026Shitian Zhao, Shaoheng Lin, Ming Li +4Adaptive Video Frame Sampling Multimodal Agents
Shanghai AI Lab · UMD · CUHK +3
Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
Feb 22, 2026Zhuoxu Huang, Mengxi Jia, Hao Sun +2RL Exploration RL for VLMs
Aberystwyth University · Institute of Artificial Intelligence (TeleAl), China Telecom · Tsinghua University
Think with Grounding: Curriculum Reinforced Reasoning with Video Grounding for Long Video Understanding
Feb 21, 2026Houlun Chen, Xin Wang, Guangyao Li +4Long-Video Understanding Video QA
Tsinghua University, Beijing, China
GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking
Feb 19, 2026Zixu Cheng, Da Li, Jian Hu +4Video SGG Video Reasoning
Queen Mary University of London · Samsung AI Centre Cambridge · Shanghai Artificial Intelligence Laboratory +1
TikArt: Stabilizing Aperture-Guided Fine-Grained Visual Reasoning with Reinforcement Learning
Feb 16, 2026Hao Ding, Zhichuan Yang, Weijie Ge +3VLM Reasoning Multimodal Reasoning
Zhejiang University, Hangzhou, China · Xi’an Jiaotong University, Xi’an, China · Zhejiang University of Science and Technology, Hangzhou, China
WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL
Feb 15, 2026Zhennan Jiang, Shangqing Zhou, Yutong Jiang +11World Models for Robotics World Models
University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences · Zhongguancun Academy +2
Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models
Feb 13, 2026Liangzhi Shi, Shuaihang Chen, Feng Gao +8VLA Model Training Sim-to-Real Transfer
Tsinghua University · Shanghai AI Laboratory · Harbin Institute of Technology +3
LongNav-R1: Horizon-Adaptive Multi-Turn RL for Long-Horizon VLA Navigation
Feb 12, 2026Yue Hu, Avery Xi, Qixin Xiao +4Robot Navigation Vision-Language Navigation
University of Michigan, Ann Arbor
Do MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs
Feb 9, 2026Siqu Ou, Tianrui Wan, Zhiyuan Zhao +2Reasoning for VLMs Attention Intervention in VLMs
TeleAI · Shanghai Jiao Tong University · Northwestern Polytechnical University
Clarify or Answer: Reinforcement Learning for Agentic VQA with Context Under-specification
Jan 23, 2026Zongwan Cao, Bingbing Wen, Lucy Lu WangVisual Question Answering Clarification Question Generation
University of Washington · Allen Institute for AI
Think3D: Thinking with Space for Spatial Reasoning
Jan 19, 2026Zaibin Zhang, Yuhan Wu, Lianjie Jia +103D Spatial Reasoning VLM Reasoning
Dalian University of Technology · University of California San Diego · Independent Researcher +1
CASHEW: Stabilizing Multimodal Reasoning via Iterative Trajectory Aggregation
Jan 12, 2026Chaoyu Li, Fei Tao, Pooyan FazliTest-Time Scaling for VLMs Test-Time Scaling
Arizona State University · NewsBreak
Mimic Human Cognition, Master Multi-Image Reasoning: A Meta-Action Framework for Enhanced Visual Understanding
Jan 12, 2026Jianghao Yin, Qingbin Li, Kun Sun +10Visual Reasoning Multimodal Reasoning
East China Normal University · ByteDance
HERO: Hierarchical Evidential Reasoning Optimization for Radiology Report Generation via Reason-then-Summarize
Jan 6, 2026Kun Zhao, Guodong Liu, Hui Ji +7Radiology Report Generation Medical VLMs
University of Pittsburgh · Eli and Lilly Company · The University of Manchester +1
From Perception to Punchline: Empowering VLM with the Art of In-the-wild Meme
Dec 31, 2025Xueyan Li, Yingyi Xue, Mengjie Jiang +2VLM Reasoning RL for VLMs
Shanghai Artificial Intelligence Laboratory · Fudan University · Columbia Engineering Columbia University +1
Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models
Nov 18, 2025Zehao Liu, Weijieying Ren, Jipeng Zhang +4VLM Robustness Medical Diagnosis
Pennsylvania State University, University Park, PA 16802, USA · Stanford University, Stanford, CA 94305, USA · Hong Kong University of Science and Technology, Hong Kong, China
SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards
Nov 10, 2025Hunar Batra, Haoqin Tu, Hardy Chen +3Multimodal Understanding Scene Graph Generation
University of Oxford · University of California, Santa Cruz
Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models
Oct 11, 2025Mingyang Lyu, Yinqian Sun, Erliang Lin +4Flow Matching Robotic Manipulation
Brain-inspired Cognitive AI Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, China. · Beijing Institute of AI Safety and Governance, China. · University of Chinese Academy of Sciences (UCAS), Beijing, China. +3
Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models using Reinforcement Learning from Ranking Feedback
Oct 2, 2025Derek Shi, Ruben Glatt, Christine Klymko +5Video-Language Models RL Fine-Tuning
Stanford University, CA, USA · Lawrence Livermore National Laboratory, CA, USA · Microsoft, WA, USA
AdaThinkDrive: Adaptive Thinking via Reinforcement Learning for Autonomous Driving
Sep 17, 2025Yuechen Luo, Fang Li, Shaoqing Xu +11Autonomous Driving Reasoning for VLA Models
Tsinghua University · Xiaomi EV · Nanyang Technological University +2
Bridging the Gap in Ophthalmic AI: MM-Retinal-Reason Dataset and OphthaReason Model toward Dynamic Multimodal Reasoning
Aug 22, 2025Ruiqi Wu, Yuang Yao, Na Su +11RL for VLMs Medical Image Analysis
School of Computer Science and Engineering, Southeast University, Nanjing, China · Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China · School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization
Aug 6, 2025Jingyi Liao, Yongyi Su, Rong-Cheng Tu +6VLM Adaptation Industrial Anomaly Detection
1Nanyang Technological University · Institute for Infocomm Research (I2R), A*STAR · 3South China University of Technology
VRPRM: Process Reward Modeling via Visual Reasoning
Aug 5, 2025Xinquan Chen, Chongying Yue, Bangwei Liu +3Process Reward Models Multimodal Reward Modeling
Shanghai AI Laboratory · Zhejiang University · East China Normal University
Multimodal Mathematical Reasoning with Diverse Solving Perspective
Jul 3, 2025Wenhao Shi, Zhiqiang Hu, Yi Bin +4Multimodal Reasoning Multimodal CoT Reasoning
Tongji University, Shanghai, China · National University of Singapore, Singapore · Tencent, Beijing, China +2

Feb 25, 2026J/K move · Enter open · S save

RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning

Yukun Chen, Jiaming Li, Longze Chen, Ze Gong+9

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Alibaba Group+1

VLM Reasoning Rubric-Based RL RL for VLMs Curriculum RL Visual Reasoning

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Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a prevailing paradigm for enhancing reasoning in Multimodal Large Language Models (MLLMs). However, relying solely on outcome supervision risks reward hacking, where models learn spurious reasoning patterns to satisfy final answer checks. While recent rubric-based approaches offer fine-grained supervision signals, they suffer from high computational costs of instance-level generation and inefficient training dynamics caused by treating all rubrics as equally learnable. In this paper, we propose Stratified Rubric-based Curriculum Learning (RuCL), a novel framework that reformulates curriculum learning by shifting the focus from data selection to reward design. RuCL generates generalized rubrics for broad applicability and stratifies them based on the model's competence. By dynamically adjusting rubric weights during training, RuCL guides the model from mastering foundational perception to tackling advanced logical reasoning. Extensive experiments on various visual reasoning benchmarks show that RuCL yields a remarkable +7.83% average improvement over the Qwen2.5-VL-7B model, achieving a state-of-the-art accuracy of 60.06%.