Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation
Yuta Kobayashi, Pradyun Ramesh, Muhammad Ahmed Chaudhry, Vincent Jeanselme, Judy Wawira Gichoya, Sanmi Koyejo, Kathleen Capaccione, Shalmali Joshi
cs.CV, cs.LG
Submitted: 2026-08-05
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Visual Alignment of Medical Vision-Language Models for Grounded Radiology Report Generation
- CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats
- Provably Robust DPO: Aligning Language Models with Noisy Feedback
- Self-Boosting Large Language Models with Synthetic Preference Data
- ChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step Verification
- How Well Can Preference Optimization Generalize Under Noisy Feedback?
- RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
- Nonparametric semi-supervised learning of class proportions
- MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
- ROPO: Robust Preference Optimization for Large Language Models
- Scaling medical imaging report generation with multimodal reinforcement learning
- RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
- Reasoning Visual Language Model for Chest X-Ray Analysis
- MedGemma Technical Report
- Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
- MRG-R1: Reinforcement Learning for Clinically Aligned Medical Report Generation
- Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
- Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint
- BERTScore: Evaluating Text Generation with BERT
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