3 papers
cs.LG2026
Compress-Distill: Reasoning Trace Compression for Efficient Knowledge Distillation
Maxime Griot, Paul Steven Scotti, Tanishq Mathew Abraham
Reasoning models produce long chain-of-thought traces that are costly to distill and encourage verbose student outputs. We study post-hoc compression of such traces before knowledg…
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
MedRiskEval: Medical Risk Evaluation Benchmark of Language Models, On the Importance of User Perspectives in Healthcare Settings
Jean-Philippe Corbeil, Minseon Kim, Maxime Griot +4
As the performance of large language models (LLMs) continues to advance, their adoption in the medical domain is increasing. However, most existing risk evaluations largely focused…