MC-CXR: A Multi-Context Chest X-ray Benchmark for Context-Induced Disruption in Vision-Language Models
cs.CL
Submitted: 2026-08-25
Updated: 2026-08-25
Comments: 15 pages, 3 figures, 4 tables. Accepted to Findings of EMNLP 2026
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation
- MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
- Reasoning Visual Language Model for Chest X-Ray Analysis
- MedGemma 1.5 Technical Report
- Qwen3.5-Omni Technical Report
- PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering