4 papers · 1 filter
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…
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…
More Questions than Answers? Lessons from Integrating Explainable AI into a Cyber-AI Tool
Ashley Suh, Harry Li, Caitlin Kenney +2
We share observations and challenges from an ongoing effort to implement Explainable AI (XAI) in a domain-specific workflow for cybersecurity analysts. Specifically, we briefly des…
Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities
Harry Li, Gabriel Appleby, Camelia Daniela Brumar +2
This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases. Thro…