7 citations · 13 across the 16 of their papers we have counts for
5 papers · 1 filter
Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval
Hamed Jelodar, Samita Bai, Mohammad Meymani +3
Generative AI, particularly Large Language Models, increasingly integrates graph-based representations to enhance reasoning, retrieval, and structured decision-making. Despite rapi…
LLM4CodeRE: Generative AI for Code Decompilation Analysis and Reverse Engineering
Hamed Jelodar, Samita Bai, Tochukwu Emmanuel Nwankwo +4
Code decompilation analysis is a fundamental yet challenging task in malware reverse engineering, particularly due to the pervasive use of sophisticated obfuscation techniques. Alt…
Automated Malware Family Classification using Weighted Hierarchical Ensembles of Large Language Models
Samita Bai, Hamed Jelodar, Tochukwu Emmanuel Nwankwo +4
Malware family classification remains a challenging task in automated malware analysis, particularly in real-world settings characterized by obfuscation, packing, and rapidly evolv…
Routing-Aware Explanations for Mixture of Experts Graph Models in Malware Detection
Hossein Shokouhinejad, Roozbeh Razavi-Far, Griffin Higgins +1
Mixture-of-Experts (MoE) offers flexible graph reasoning by combining multiple views of a graph through a learned router. We investigate routing-aware explanations for MoE graph mo…
Transparent Malware Detection With Granular Assembly Flow Explainability via Graph Neural Networks
Griffin Higgins, Roozbeh Razavi-Far, Hossein Shokouhinejad +1
As malware continues to become increasingly sophisticated, threatening, and evasive, malware detection systems must keep pace and become equally intelligent, powerful, and transpar…