3 papers
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
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.LG2025
Scaling laws for activation steering with Llama 2 models and refusal mechanisms
Sheikh Abdur Raheem Ali, Justin Xu, Ivory Yang +3
As large language models (LLMs) evolve in complexity and capability, the efficacy of less widely deployed alignment techniques are uncertain. Building on previous work on activatio…