NCBI PubMed Central
open access
Hallucination filtering in radiology vision-language models using discrete semantic entropy.
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
- Detecting hallucinations in large language models using semantic entropy#16577
- SelfCheck-Eval: A multi-module framework for zero-resource hallucination detection in large language models.#297476
- On the transfer learning behavior of domain-specific vision-language models in screening mammography.#312500
- Swin-Qwen3: a three-stage vision-language framework for automated radiology report generation with multi-agent verification.#449933
- Refining Cytology Predictions with Conditional Random Fields#1105586
Record · ID 298868
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