3 papers
cs.LG2026
When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models
Ding Zhang, Runtao Zhou, Wenqing Zheng +3
Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to graph learning tasks. By transforming graph topology and node informatio…
cs.HC2025
Improving Human Verification of LLM Reasoning through Interactive Explanation Interfaces
Runtao Zhou, Giang Nguyen, Nikita Kharya +2
The reasoning capabilities of Large Language Models (LLMs) have led to their increasing employment in several critical applications, particularly education, where they support prob…
cs.CL2025
Disparities in LLM Reasoning Accuracy and Explanations: A Case Study on African American English
Runtao Zhou, Guangya Wan, Saadia Gabriel +4
Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning tasks, leading to their widespread deployment. However, recent studies have highlighted concerni…