7 papers
Equitable System-Prompt Selection via Constrained Mixed-Strategy GroupDRO
Mengyu Xu, Qiaoxin Yang, Zhihan Liu +4
Large language models are increasingly used for information seeking, yet semantically equivalent questions phrased in different ways can receive answers of considerably different q…
Rethinking LLM-Judged Helpfulness as a Pedagogy Signal: A Pre-Registered Audit Across Tutor Models
Shuyi Fan, Boyuan Deng, Mengyu Xu +4
LLM tutoring poses a measurement problem: can a general-purpose helpfulness rubric distinguish direct answer-giving from pedagogical guidance? We audit this signal in a pre-registe…
MIRA: A Bilingual Benchmark for Medical Information Response Audit
Mengyu Xu, Qiaoxin Yang, Qianqian Wang +3
Existing safety evaluations for large language models overlook whether responses preserve comparable medical information across different user phrasings of the same question. To ad…
Classroom Final Exam: An Instructor-Tested Reasoning Benchmark
Chongyang Gao, Diji Yang, Shuyan Zhou +4
We introduce CFE-Bench (Classroom Final Exam), a multimodal benchmark for evaluating the reasoning capabilities of large language models across more than 20 STEM domains. CFE-Bench…
Exploiting Label-Independent Regularization from Spatial Dependencies for Whole Slide Image Analysis
Weiyi Wu, Xinwen Xu, Chongyang Gao +3
Whole slide images, with their gigapixel-scale panoramas of tissue samples, are pivotal for precise disease diagnosis. However, their analysis is hindered by immense data size and…
Assessing and Mitigating Medical Knowledge Drift and Conflicts in Large Language Models
Weiyi Wu, Xinwen Xu, Chongyang Gao +4
Large Language Models (LLMs) have great potential in the field of health care, yet they face great challenges in adapting to rapidly evolving medical knowledge. This can lead to ou…
Learning Spatial-Preserving Hierarchical Representations for Digital Pathology
Weiyi Wu, Xingjian Diao, Chunhui Zhang +4
Whole slide images (WSIs) pose fundamental computational challenges due to their gigapixel resolution and the sparse distribution of informative regions. Existing approaches often…