3 papers
cs.CL2026
Are LLMs Ready to Assist Physicians? PhysAssistBench for Interactive Doctor-Patient-EHR Assistance
Tianming Du, Peijie Yu, Sihan Shang +12
The most plausible near-term role of medical LLMs is to assist rather than replace physicians, yet current evaluations often test isolated capabilities: clinical knowledge, EHR sys…
cs.CV2026
DDX-TRACE: A Benchmark for Medical Diagnostic Trajectories in VLMs
Jiazhen Pan, Weixiang Shen, Jun Li +7
Medical diagnosis is not a single prediction from a fully specified vignette. It is a sequential workup: clinicians decide what evidence to obtain, revise a differential diagnosis,…
cs.CV2026
Learning to Read Where to Look: Disease-Aware Vision-Language Pretraining for 3D CT
Simon Ging, Philipp Arnold, Sebastian Walter +6
Recent 3D CT vision-language models align volumes with reports via contrastive pretraining, but typically rely on limited public data and provide only coarse global supervision. We…