Multimodal Reward Modeling

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5 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Latest papers 59

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MT-EditFlow: Reinforcement Learning for Multi-Turn Image Editing with Flow Matching
Jun 1, 2026Jiahui Huang, Yasi Zhang, Tianyu Chen +6Multimodal Reward Modeling RL for Generative Models
Apple · University of California, Los Angeles · University of Texas at Austin +1
MuPHI: Learning Implicit Multimodal Harm Reasoning via Semantically Grounded Reward Optimization
May 28, 2026Anisha Saha, Varsha Suresh, Teodora Kamova +3VLM Robustness Multimodal Reasoning
Max Planck Institute for Informatics, Saarland Informatics Campus · Saarland University · The University of Edinburgh +1
Refining Multidimensional Video Reward Models via Disentangled Influence Functions
May 27, 2026Muyao Wang, Zeke Xie, Hideki NakayamaReward Modeling Training Data Selection
The University of Tokyo · HKUST (Guangzhou)
VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning
May 27, 2026Xingyu Lu, Jinpeng Wang, Yi-Fan Zhang +13Image Captioning Object Hallucination in VLMs
1Tsinghua Shenzhen International Graduate School · 2Harbin Institute of Technology, Shenzhen · 3Chinese Academy of Sciences +1
DyCoRM: Dynamic Criterion-Aware Reward Modeling for Text-to-Image Generation
May 25, 2026Jiaying Qian, Ziheng Jia, Qian Zhang +5Reward Modeling T2I Generation
Shanghai Jiao Tong University
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
May 22, 2026Christian Gumbsch, Leonardo Barcellona, Lennard Schünemann +7RL for Robotics Multimodal Reward Modeling
University of Amsterdam · 2Catholic University of Leuven · 3Toyota Research Institute +1
Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling
May 13, 2026Xuehai Bai, Yang Shi, Yi-Fan Zhang +7Reward Modeling Image Editing Evaluation
HDU · PKU · Kling Team +1
CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
May 12, 2026Jiyuan Wang, Huan Ouyang, Jiuzhou Lin +15Temporal Video Grounding Multimodal Reward Modeling
BJTU · NTU · BUPT +1
DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification
May 10, 2026Rui Liu, Dian Yu, Zhenwen Liang +6Multimodal Large Language Models Multimodal Reward Modeling
1Tencent Hunyuan · University of Maryland, College Park · University of North Carolina, Chapel Hill
ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation
May 9, 2026Youhe Feng, Hansen Shi, Haoyang Li +7Long-Horizon Robotic Manipulation Multimodal Reward Modeling
School of Information, Renmin University of China · Work done during the internship at Zhipu AI. · Zhipu AI +1
RewardHarness: Self-Evolving Agentic Post-Training
May 9, 2026Yuxuan Zhang, Penghui Du, Bo Li +11Reward Modeling Image Editing Evaluation
University of British Columbia · Kolors Team, Kuaishou Technology · University of Waterloo +4
Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria
May 8, 2026Juanxi Tian, Fengyuan Liu, Jiaming Han +6Policy Optimization Multimodal Reward Modeling
1Nanyang Technological University · 2Ant Group · 3MMLab, The Chinese University of Hong Kong +1
Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models
May 8, 2026Yuancheng Wei, Linli Yao, Lei Li +4Reward Modeling Multimodal Reward Modeling
South China University of Technology · Peking University · The University of Hong Kong +1
ReasonEdit: Towards Interpretable Image Editing Evaluation via Reinforcement Learning
May 8, 2026Honghua Chen, Zitong Xu, Huiyu Duan +3Image Editing Evaluation Text-Guided Image Editing
University of Electronic Science and Technology of China · 2Shanghai Jiao Tong University
Think, then Score: Decoupled Reasoning and Scoring for Video Reward Modeling
May 7, 2026Yuan Wang, Ouxiang Li, Yulong Xu +8Reward Modeling Multimodal Reward Modeling
University of Science and Technology of China · Kling Team, Kuaishou Technology · Institute of Software Chinese Academy of Sciences
RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
May 5, 2026Hao Wu, Yuqi Li, Yuan Gao +10Multimodal Reward Modeling World Model Evaluation
Tencent · Tsinghua University · Department of Computer Science, City University of New York +3
ProMMSearchAgent: A Generalizable Multimodal Search Agent Trained with Process-Oriented Rewards
Apr 22, 2026Wentao Yan, Shengqin Wang, Huichi Zhou +4Multimodal IR Process Reward Models
East China Normal University · Huawei Noah’s Ark Lab · University College London +2
DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling
Apr 21, 2026Zhihong Zhang, Jie Zhao, Xiaojian Huang +5Multimodal Reward Modeling Preference Learning
University of Science and Technology of China
Lost in Translation: Do LVLM Judges Generalize Across Languages?
Apr 21, 2026Md Tahmid Rahman Laskar, Mohammed Saidul Islam, Mir Tafseer Nayeem +5VLM Evaluation Multilingual VLM Evaluation
York University · University of Alberta · Nanyang Technological University +1
Prioritizing the Best: Incentivizing Reliable Multimodal Reasoning by Rewarding Beyond Answer Correctness
Apr 20, 2026Mengzhao Jia, Zhihan Zhang, Meng JiangMultimodal Reasoning Multimodal Reward Modeling
University of Notre Dame
DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving
Mar 18, 2026Zilin Huang, Zihao Sheng, Zhengyang Wan +4VLMs for Autonomous Driving LLM-Guided RL
Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA · Lyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN 47907, USA · Department of Civil Engineering, McGill University, Montreal, QC, H3A 0C3, Canada
Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models
Mar 17, 2026Yanru Wu, Weiduo Yuan, Esteban Martinez Licon +4Long-Horizon Robotic Manipulation Robot Skill Learning
USC Physical Superintelligence Lab
Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models
Feb 7, 2026Yankai Yang, Yancheng Long, Hongyang Wei +12Reward Modeling Multimodal Reward Modeling
Harbin Institute of Technology, Shenzhen. · Kuaishou Technology.
Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis
Jan 31, 2026Zicheng Kong, Dehua Ma, Zhenbo Xu +9Reward Modeling RL for Language Models
Beijing University of Posts and Telecommunications, Beijing, P.R. China · ShiFang Technology Inc., Hangzhou, P.R. China · Tsinghua University, Beijing, P.R. China +1
Understanding Reward Hacking in Text-to-Image Reinforcement Learning
Jan 6, 2026Yunqi Hong, Kuei-Chun Kao, Hengguang Zhou +1Reward Hacking Multimodal Reward Modeling
Department of Computer Science, University of California, Los Angeles
RubricRL: Simple Generalizable Rewards for Text-to-Image Generation
Nov 25, 2025Xuelu Feng, Yunsheng Li, Ziyu Wan +4Reward Modeling T2I Generation
University at Buffalo · Microsoft AI · Nikola Tesla STEM High School
Rethinking Reward Signals in Video GRPO: When Scores Become Targets
Nov 24, 2025Rui Li, Yuanzhi Liang, Ziqi Ni +3Reward Hacking RL for Video Generation
University of Science and Technology of China, Hefei, China · Institute of Artificial Intelligence (TeleAI), China Telecom, Shanghai, China · Southeast University, Nanjing, China
SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models
Oct 14, 2025Weiyang Jin, Yuwei Niu, Jiaqi Liao +4Unified Multimodal Models T2I Generation
HKU MMLab · The University of Hong Kong · Shenzhen Loop Area Institute +2
GUI-PRA: Process Reward Agent for GUI Tasks
Sep 27, 2025Tao Xiong, Xavier Hu, Yurun Chen +6Process Reward Models GUI Agents
Zhejiang University · MiLM Plus, Xiaomi Inc.

Jun 1, 2026, cs.CVJ/K move · Enter open · S save

MT-EditFlow: Reinforcement Learning for Multi-Turn Image Editing with Flow Matching

Jiahui Huang, Yasi Zhang, Tianyu Chen, Shu Wang+5

Apple · University of California, Los Angeles · University of Texas at Austin+1

Multimodal Reward Modeling RL for Generative Models Diffusion-Based Image Editing Image Editing RL for Image Editing

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Recent breakthroughs in instruction-based image editing have captured significant attention, as models are now capable of handling real-world editing demands with the practicality required by everyday users. However, editing models trained primarily for single-turn edits often break down in multi-turn editing--the natural interactive setting where a user iteratively refines an image based on the model's own previous outputs. This failure stems from the all-or-nothing requirement, where a single failed turn compromises the entire sequence, and error propagation, where exposure bias leads to compounding editing errors. To address these challenges, we introduce MT-EditFlow, a flow-matching reinforcement learning framework designed to optimize reward signals for sequential image editing. MT-EditFlow integrates a multi-turn perspective with a multi-reward formulation to provide a unified structure applicable to both GRPO and NFT-based reinforcement learning methods. We systematically analyze and optimize the reward signal by investigating effective scoring strategies for turn-level aggregation, VLM reasoning modes to trade off reward bias and variance, and advantage fusion levels to prevent reward hacking. Our findings reveal that broadcasting the aggregated advantage across the entire editing trajectory effectively bridges the gap between local planning and global multi-turn task success. Extensive experiments demonstrate that MT-EditFlow significantly improves performance across diverse base models. Notably, it boosts FLUX.1-Kontext-dev by 6.85 points in turn-3 overall performance, surpassing state-of-the-art open-source models such as Qwen-Image-Edit. By maintaining high marginal success rates and reducing exposure bias, MT-EditFlow provides a foundation for more reliable and natural human-AI collaboration in visual content creation.

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