大模型对齐与安全

Beyond the Leaderboard: Understanding Performance Disparities in Large Language Models via Model Diffing

Sabri Boughorbel, Fahim Dalvi, Nadir Durrani, Majd Hawasly

机构 * Qatar Computing Research Institute, HBKU（卡塔尔计算研究所，哈瓦那大学） 纠错

专题命中 幻觉与事实性 ：safety(abstract)；分类 cs.CL

Comments 12 pages, accepted to the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)

Position Paper: Integrating Explainability and Uncertainty Estimation in Medical AI

Xiuyi Fan

机构 * Lee Kong Chian School of Medicine, College of Computing ； Data Science, Nanyang Technological University, Singapore 纠错

专题命中 幻觉与事实性 ：trustworthy(abstract)；分类 cs.AI

Comments Accepted at the International Joint Conference on Neural Networks, IJCNN 2025

Accounting for Uncertainty in Machine Learning Surrogates: A Gauss-Hermite Quadrature Approach to Reliability Analysis

Amirreza Tootchi, Xiaoping Du

专题命中 幻觉与事实性 ：trustworthy(abstract)；分类 cs.LG