arXiv (All)
open access
Visually Irrelevant Hallucinations in Medical Vision-Language Models
Medical vision-language models (VLMs) show strong performance in radiology report generation (RRG) and medical visual question answering (Med-VQA), producing free-form clinical descriptions and answers from medical images. However, they may generate clinically meaningful statements that lack visual
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Enhancing RAG-based Medical VQA with Gated Multimodal Representations#1387854
- MedGround: Bridging the Evidence Gap in Medical Vision-Language Models with Verified Grounding Data#974296
- Calibrated Confidence Expression for Radiology Report Generation#1052115
- MedVision: Benchmarking Quantitative Medical Image Analysis#793520
- MedVision: Benchmarking Quantitative Medical Image Analysis#789516
Record · ID 1489181
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive