15 citations · 17 across the 5 of their papers we have counts for
5 papers
DefenderBench: A Toolkit for Evaluating Language Agents in Cybersecurity Environments
Chiyu Zhang, Marc-Alexandre Cote, Michael Albada +6
Large language model (LLM) agents have shown impressive capabilities in human language comprehension and reasoning, yet their potential in cybersecurity remains underexplored. We i…
Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations
Ishani Mondal, Jack W. Stokes, Sujay Kumar Jauhar +5
LLMs often fail to meet the specialized needs of distinct user groups due to their one-size-fits-all training paradigm \cite{lucy-etal-2024-one} and there is limited research on wh…
AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks
Jiacen Xu, Jack W. Stokes, Geoff McDonald +5
Large language models (LLMs) have demonstrated impressive results on natural language tasks, and security researchers are beginning to employ them in both offensive and defensive s…
Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models
Ying-Chun Lin, Jennifer Neville, Jack W. Stokes +14
Accurate and interpretable user satisfaction estimation (USE) is critical for understanding, evaluating, and continuously improving conversational systems. Users express their sati…
Heterogeneous Graph Neural Network on Semantic Tree
Mingyu Guan, Jack W. Stokes, Qinlong Luo +4
The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to em…