collaborators

5 papers

cs.AI2025

Limits of Emergent Reasoning of Large Language Models in Agentic Frameworks for Deterministic Games

Chris Su, Harrison Li, Matheus Marques +3

Recent work reports that Large Reasoning Models (LRMs) undergo a collapse in performance on solving puzzles beyond certain perplexity thresholds. In subsequent discourse, questions…

cs.LG2025

The Role of Visualization in LLM-Assisted Knowledge Graph Systems: Effects on User Trust, Exploration, and Workflows

Harry Li, Gabriel Appleby, Kenneth Alperin +2

Knowledge graphs (KGs) are powerful data structures, but exploring them effectively remains difficult for even expert users. Large language models (LLMs) are increasingly used to a…

cs.HC2025

Don't Just Translate, Agitate: Using Large Language Models as Devil's Advocates for AI Explanations

Ashley Suh, Kenneth Alperin, Harry Li +1

This position paper highlights a growing trend in Explainable AI (XAI) research where Large Language Models (LLMs) are used to translate outputs from explainability techniques, lik…

cs.HC2025

Mitigating LLM Hallucinations with Knowledge Graphs: A Case Study

Harry Li, Gabriel Appleby, Kenneth Alperin +2

High-stakes domains like cyber operations need responsible and trustworthy AI methods. While large language models (LLMs) are becoming increasingly popular in these domains, they s…

cs.CL2025

LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering

Harry Li, Gabriel Appleby, Ashley Suh

We present LinkQ, a system that leverages a large language model (LLM) to facilitate knowledge graph (KG) query construction through natural language question-answering. Traditiona…