Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Lai, Yuxiang, Zhong, Jike, Li, Ming, Zhao, Shitian, Li, Yuheng, Psounis, Konstantinos, Yang, Xiaofeng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Context Matters: Learning Global Semantics via Object-Centric Representation
by: Zhong, Jike, et al.
Published: (2025)
by: Zhong, Jike, et al.
Published: (2025)
Are Video Models Emerging as Zero-Shot Learners and Reasoners in Medical Imaging?
by: Lai, Yuxiang, et al.
Published: (2025)
by: Lai, Yuxiang, et al.
Published: (2025)
TIR-Bench: A Comprehensive Benchmark for Agentic Thinking-with-Images Reasoning
by: Li, Ming, et al.
Published: (2025)
by: Li, Ming, et al.
Published: (2025)
MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting
by: Li, Yuheng, et al.
Published: (2025)
by: Li, Yuheng, et al.
Published: (2025)
EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark
by: Li, Ming, et al.
Published: (2024)
by: Li, Ming, et al.
Published: (2024)
VRIQ: Benchmarking and Analyzing Visual-Reasoning IQ of VLMs
by: Khezresmaeilzadeh, Tina, et al.
Published: (2026)
by: Khezresmaeilzadeh, Tina, et al.
Published: (2026)
Think or Not Think: A Study of Explicit Thinking in Rule-Based Visual Reinforcement Fine-Tuning
by: Li, Ming, et al.
Published: (2025)
by: Li, Ming, et al.
Published: (2025)
Patient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy
by: Lai, Yuxiang, et al.
Published: (2025)
by: Lai, Yuxiang, et al.
Published: (2025)
MedDINOv3: How to adapt vision foundation models for medical image segmentation?
by: Li, Yuheng, et al.
Published: (2025)
by: Li, Yuheng, et al.
Published: (2025)
MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering
by: Xi, Suyang, et al.
Published: (2026)
by: Xi, Suyang, et al.
Published: (2026)
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning
by: Pan, Jiazhen, et al.
Published: (2025)
by: Pan, Jiazhen, et al.
Published: (2025)
EchoVLM: Measurement-Grounded Multimodal Learning for Echocardiography
by: Li, Yuheng, et al.
Published: (2025)
by: Li, Yuheng, et al.
Published: (2025)
MedSeg-R: Reasoning Segmentation in Medical Images with Multimodal Large Language Models
by: Huang, Yu, et al.
Published: (2025)
by: Huang, Yu, et al.
Published: (2025)
Med3D-R1: Incentivizing Clinical Reasoning in 3D Medical Vision-Language Models for Abnormality Diagnosis
by: Lai, Haoran, et al.
Published: (2026)
by: Lai, Haoran, et al.
Published: (2026)
Affordance-R1: Reinforcement Learning for Generalizable Affordance Reasoning in Multimodal Large Language Model
by: Wang, Hanqing, et al.
Published: (2025)
by: Wang, Hanqing, et al.
Published: (2025)
MedReason-R1: Learning to Reason for CT Diagnosis with Reinforcement Learning and Local Zoom
by: Li, Yifan, et al.
Published: (2025)
by: Li, Yifan, et al.
Published: (2025)
ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models
by: Song, Zirui, et al.
Published: (2025)
by: Song, Zirui, et al.
Published: (2025)
Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification
by: Li, Ming, et al.
Published: (2024)
by: Li, Ming, et al.
Published: (2024)
Vision-Language Semantic Aggregation Leveraging Foundation Model for Generalizable Medical Image Segmentation
by: Yu, Wenjun, et al.
Published: (2025)
by: Yu, Wenjun, et al.
Published: (2025)
MedFact-R1: Towards Factual Medical Reasoning via Pseudo-Label Augmentation
by: Li, Gengliang, et al.
Published: (2025)
by: Li, Gengliang, et al.
Published: (2025)
MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation
by: Koleilat, Taha, et al.
Published: (2026)
by: Koleilat, Taha, et al.
Published: (2026)
On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?
by: Imam, Raza, et al.
Published: (2025)
by: Imam, Raza, et al.
Published: (2025)
PyVision-RL: Forging Open Agentic Vision Models via RL
by: Zhao, Shitian, et al.
Published: (2026)
by: Zhao, Shitian, et al.
Published: (2026)
TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models
by: Zhang, Junyi, et al.
Published: (2025)
by: Zhang, Junyi, et al.
Published: (2025)
Med-StepBench: A Hierarchical Reasoning Framework for Evaluating Hallucinations in Medical Vision-Language Models
by: Nguyen, Minh Khoi, et al.
Published: (2026)
by: Nguyen, Minh Khoi, et al.
Published: (2026)
Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning of Vision Language Models
by: Tan, Huajie, et al.
Published: (2025)
by: Tan, Huajie, et al.
Published: (2025)
MedSeg-R: Medical Image Segmentation with Clinical Reasoning
by: Shao, Hao, et al.
Published: (2025)
by: Shao, Hao, et al.
Published: (2025)
VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
by: Yang, Senqiao, et al.
Published: (2025)
by: Yang, Senqiao, et al.
Published: (2025)
Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning
by: Zhan, Yufei, et al.
Published: (2025)
by: Zhan, Yufei, et al.
Published: (2025)
Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
by: Jiang, Songtao, et al.
Published: (2025)
by: Jiang, Songtao, et al.
Published: (2025)
VLA-R1: Enhancing Reasoning in Vision-Language-Action Models
by: Ye, Angen, et al.
Published: (2025)
by: Ye, Angen, et al.
Published: (2025)
PeRL: Permutation-Enhanced Reinforcement Learning for Interleaved Vision-Language Reasoning
by: Zhang, Yizhen, et al.
Published: (2025)
by: Zhang, Yizhen, et al.
Published: (2025)
MultiMedVision: Multi-Modal Medical Vision Framework
by: Li, Frank, et al.
Published: (2026)
by: Li, Frank, et al.
Published: (2026)
MedFoundationHub: A Lightweight and Secure Toolkit for Deploying Medical Vision Language Foundation Models
by: Li, Xiao, et al.
Published: (2025)
by: Li, Xiao, et al.
Published: (2025)
GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning
by: Su, Yanzhou, et al.
Published: (2025)
by: Su, Yanzhou, et al.
Published: (2025)
MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
by: Kim, Soo Yong, et al.
Published: (2025)
by: Kim, Soo Yong, et al.
Published: (2025)
Towards Universal Text-driven CT Image Segmentation
by: Li, Yuheng, et al.
Published: (2025)
by: Li, Yuheng, et al.
Published: (2025)
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
by: Saremi, Parham, et al.
Published: (2025)
by: Saremi, Parham, et al.
Published: (2025)
Boosting the Generalization and Reasoning of Vision Language Models with Curriculum Reinforcement Learning
by: Deng, Huilin, et al.
Published: (2025)
by: Deng, Huilin, et al.
Published: (2025)
Med-Evo: Test-time Self-evolution for Medical Multimodal Large Language Models
by: Xu, Dunyuan, et al.
Published: (2026)
by: Xu, Dunyuan, et al.
Published: (2026)
Similar Items
-
Context Matters: Learning Global Semantics via Object-Centric Representation
by: Zhong, Jike, et al.
Published: (2025) -
Are Video Models Emerging as Zero-Shot Learners and Reasoners in Medical Imaging?
by: Lai, Yuxiang, et al.
Published: (2025) -
TIR-Bench: A Comprehensive Benchmark for Agentic Thinking-with-Images Reasoning
by: Li, Ming, et al.
Published: (2025) -
MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting
by: Li, Yuheng, et al.
Published: (2025) -
EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark
by: Li, Ming, et al.
Published: (2024)