6 papers
RPAM: A Principled Metric for Evaluating Associations in Language Models with High Predictive Validity in Downstream Outputs
Damian Hodel, Jevin West, Aylin Caliskan
Language models (LMs) exhibit problematic biases, such as stereotypes. Effectively analyzing and mitigating such biases requires accurate and generalizable evaluation methods of th…
Training LLMs with Reinforcement Learning for Intent-Aware Personalized Question Answering
Maryam Amirizaniani, Benjamin Charles Germain Lee, Jevin West +1
Effective personalized question answering (PQA) in language models requires grounding responses in the user's underlying intent, where intent refers to the implicit ``why'' behind…
The Cost of Consensus: Malignant Epistemic Herding and Adaptive Gating in Distributed Multi-Agent Search
David Farr, Iain Cruickshank, Kate Starbird +1
Distributed agents in real-world settings frequently must coordinate under uncertainty with only partial observations. Coordination is necessary to share beliefs to aid in task com…
Temporal Narrative Monitoring in Dynamic Information Environments
David Farr, Stephen Prochaska, Jack Moody +4
Comprehending the information environment (IE) during crisis events is challenging due to the rapid change and abstract nature of the domain. Many approaches focus on snapshots via…
Simulating Misinformation Vulnerabilities With Agent Personas
David Farr, Lynnette Hui Xian Ng, Stephen Prochaska +2
Disinformation campaigns can distort public perception and destabilize institutions. Understanding how different populations respond to information is crucial for designing effecti…
Expert-in-the-Loop Systems with Cross-Domain and In-Domain Few-Shot Learning for Software Vulnerability Detection
David Farr, Kevin Talty, Alexandra Farr +3
As cyber threats become more sophisticated, rapid and accurate vulnerability detection is essential for maintaining secure systems. This study explores the use of Large Language Mo…