Cover Image

Med-RewardBench: Benchmarking Reward Models and Judges for Medical Multimodal Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ding, Meidan, Zhang, Jipeng, Wang, Wenxuan, Li, Cheng-Yi, Fang, Wei-Chieh, Wu, Hsin-Yu, Zhong, Haiqin, Chen, Wenting, Shen, Linlin
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MMedExpert-R1: Strengthening Multimodal Medical Reasoning via Domain-Specific Adaptation and Clinical Guideline Reinforcement
by: Ding, Meidan, et al.
Published: (2026)

IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation
by: Wen, Bosi, et al.
Published: (2026)

RewardBench 2: Advancing Reward Model Evaluation
by: Malik, Saumya, et al.
Published: (2025)

Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models
by: Yasunaga, Michihiro, et al.
Published: (2025)

Multimodal RewardBench 2: Evaluating Omni Reward Models for Interleaved Text and Image
by: Hu, Yushi, et al.
Published: (2025)

VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models
by: Li, Lei, et al.
Published: (2024)

M-RewardBench: Evaluating Reward Models in Multilingual Settings
by: Gureja, Srishti, et al.
Published: (2024)

Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models
by: Chen, Wenting, et al.
Published: (2025)

RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment
by: Jin, Zhuoran, et al.
Published: (2024)

Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
by: Ma, Qiyao, et al.
Published: (2026)

Long-form RewardBench: Evaluating Reward Models for Long-form Generation
by: Huang, Hui, et al.
Published: (2026)

Agent-RewardBench: Towards a Unified Benchmark for Reward Modeling across Perception, Planning, and Safety in Real-World Multimodal Agents
by: Men, Tianyi, et al.
Published: (2025)

Explainable AI-Generated Image Detection RewardBench
by: Yang, Michael, et al.
Published: (2025)

CMI-RewardBench: Evaluating Music Reward Models with Compositional Multimodal Instruction
by: Ma, Yinghao, et al.
Published: (2026)

RewardBench: Evaluating Reward Models for Language Modeling
by: Lambert, Nathan, et al.
Published: (2024)

WSI-LLaVA: A Multimodal Large Language Model for Whole Slide Image
by: Liang, Yuci, et al.
Published: (2024)

Benchmarking Egocentric Clinical Intent Understanding Capability for Medical Multimodal Large Language Models
by: Liu, Shaonan, et al.
Published: (2026)

A Spectrum Evaluation Benchmark for Medical Multi-Modal Large Language Models
by: Liu, Jie, et al.
Published: (2024)

Judge Model for Large-scale Multimodality Benchmarks
by: Shih, Min-Han, et al.
Published: (2026)

MedPRMBench: A Fine-grained Benchmark for Process Reward Models in Medical Reasoning
by: Wu, Lingyan, et al.
Published: (2026)

MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models
by: Tang, Zecheng, et al.
Published: (2026)

CliMedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models in Clinical Scenarios
by: Ouyang, Zetian, et al.
Published: (2024)

FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs
by: Wang, Xiaoqin, et al.
Published: (2025)

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
by: Chen, Zhaorun, et al.
Published: (2024)

MedEinst: Benchmarking the Einstellung Effect in Medical LLMs through Counterfactual Differential Diagnosis
by: Chen, Wenting, et al.
Published: (2026)

VerifyBench: Benchmarking Reference-based Reward Systems for Large Language Models
by: Yan, Yuchen, et al.
Published: (2025)

VideoRewardBench: Comprehensive Evaluation of Multimodal Reward Models for Video Understanding
by: Zhang, Zhihong, et al.
Published: (2025)

Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications
by: Wang, Wenxuan, et al.
Published: (2025)

RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style
by: Liu, Yantao, et al.
Published: (2024)

Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards
by: Yun, Jaehoon, et al.
Published: (2025)

MedBench v4: A Robust and Scalable Benchmark for Evaluating Chinese Medical Language Models, Multimodal Models, and Intelligent Agents
by: Ding, Jinru, et al.
Published: (2025)

Skywork-VL Reward: An Effective Reward Model for Multimodal Understanding and Reasoning
by: Wang, Xiaokun, et al.
Published: (2025)

R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning
by: Zhang, Yi-Fan, et al.
Published: (2025)

Training Data Efficiency in Multimodal Process Reward Models
by: Li, Jinyuan, et al.
Published: (2026)

AdaJudge: Adaptive Multi-Perspective Judging for Reward Modeling
by: Miao, Yongliang, et al.
Published: (2026)

MedHallBench: A New Benchmark for Assessing Hallucination in Medical Large Language Models
by: Zuo, Kaiwen, et al.
Published: (2024)

MedBench-IT: A Comprehensive Benchmark for Evaluating Large Language Models on Italian Medical Entrance Examinations
by: Lazzaroni, Ruggero Marino, et al.
Published: (2025)

MedAgentsBench: Benchmarking Thinking Models and Agent Frameworks for Complex Medical Reasoning
by: Tang, Xiangru, et al.
Published: (2025)

reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs
by: Wu, Zhaofeng, et al.
Published: (2025)

BaseReward: A Strong Baseline for Multimodal Reward Model
by: Zhang, Yi-Fan, et al.
Published: (2025)