3 papers
cs.CL2026
A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models
Michail Mamalakis, Tiago Azevedo, Cristian Cosentino +5
Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer disease, where early and trustworthy pre…
cs.CL2026
IntelliAsk: Learning to Ask High-Quality Research Questions via RLVR
Karun Sharma, Vidushee Vats, Shengzhi Li +3
Peer review relies on substantive, evidence-based questions, yet current LLMs generate surface-level queries that perform worse than human reviewer questions in expert evaluation.…
cs.LG2026
How to make Medical AI Systems safer? Simulating Vulnerabilities, and Threats in Multimodal Medical RAG System
Kaiwen Zuo, Zelin Liu, Raman Dutt +4
Large Vision-Language Models (LVLMs) augmented with Retrieval-Augmented Generation (RAG) are increasingly employed in medical AI to enhance factual grounding through external clini…