3 citations · 5 across the 3 of their papers we have counts for
4 papers
2.5-D Decomposition for LLM-Based Spatial Construction
Paul Whitten, Li-Jen Chen, Sharath Baddam
Autonomous systems that build structures from natural-language instructions need reliable spatial reasoning, yet large language models (LLMs) make systematic coordinate errors when…
Explainability Methods for Hardware Trojan Detection: A Systematic Comparison
Paul Whitten, Francis Wolff, Chris Papachristou
Hardware trojans are malicious circuits which compromise the functionality and security of an integrated circuit (IC). These circuits are manufactured directly into the silicon and…
An AI Architecture with the Capability to Classify and Explain Hardware Trojans
Paul Whitten, Francis Wolff, Chris Papachristou
Hardware trojan detection methods, based on machine learning (ML) techniques, mainly identify suspected circuits but lack the ability to explain how the decision was arrived at. An…
An AI Architecture with the Capability to Explain Recognition Results
Paul Whitten, Francis Wolff, Chris Papachristou
Explainability is needed to establish confidence in machine learning results. Some explainable methods take a post hoc approach to explain the weights of machine learning models, o…