works on

From the 2 of 25 linked papers with an AI index.

activity
20242026
most citedMerlin: A Computed Tomography Vision-Language Foundation Model and Dataset

23 citations · 23 across the 10 of their papers we have counts for

collaborators
Showing cs.CLShow all

11 papers · 1 filter

cs.CL2026

Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks

Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32

Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insufficient coverage of relevant…

cs.CL2025

Improving the Performance of Radiology Report De-identification with Large-Scale Training and Benchmarking Against Cloud Vendor Methods

Eva Prakash, Maayane Attias, Pierre Chambon +5

Objective: To enhance automated de-identification of radiology reports by scaling transformer-based models through extensive training datasets and benchmarking performance against…

cs.CL2025

Evaluating Reasoning Faithfulness in Medical Vision-Language Models using Multimodal Perturbations

Johannes Moll, Markus Graf, Tristan Lemke +7

Vision-language models (VLMs) often produce chain-of-thought (CoT) explanations that sound plausible yet fail to reflect the underlying decision process, undermining trust in high-…

cs.CL2025

Process Reward Models for Sentence-Level Verification of LVLM Radiology Reports

Alois Thomas, Maya Varma, Jean-Benoit Delbrouck +1

Automating radiology report generation with Large Vision-Language Models (LVLMs) holds great potential, yet these models often produce clinically critical hallucinations, posing se…

cs.CL2025

RadEval: A framework for radiology text evaluation

Justin Xu, Xi Zhang, Javid Abderezaei +9

We introduce RadEval, a unified, open-source framework for evaluating radiology texts. RadEval consolidates a diverse range of metrics, from classic n-gram overlap (BLEU, ROUGE) an…

cs.CL2025

Structuring Radiology Reports: Challenging LLMs with Lightweight Models

Johannes Moll, Louisa Fay, Asfandyar Azhar +5

Radiology reports are critical for clinical decision-making but often lack a standardized format, limiting both human interpretability and machine learning (ML) applications. While…