3 papers
cs.LG2026
GraphOmni: A Comprehensive and Extensible Benchmark Framework for Large Language Models on Graph-theoretic Tasks
Hao Xu, Xiangru Jian, Xinjian Zhao +9
This paper introduces GraphOmni, a comprehensive benchmark designed to evaluate the reasoning capabilities of LLMs on graph-theoretic tasks articulated in natural language. GraphOm…
q-bio.TO2025
Neu-RadBERT for Enhanced Diagnosis of Brain Injuries and Conditions
Manpreet Singh, Sean Macrae, Pierre-Marc Williams +6
Objective: We sought to develop a classification algorithm to extract diagnoses from free-text radiology reports of brain imaging performed in patients with acute respiratory failu…
cs.CL2025
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Suyuchen Wang, Jinlin Wang, Xinyu Wang +6
Large language models (LLMs) often struggle with context fidelity, producing inconsistent answers when responding to questions based on provided information. Existing approaches ei…