6 citations · 7 across the 4 of their papers we have counts for
4 papers
A Unifying Human-Centered AI Fairness Framework
Munshi Mahbubur Rahman, Shimei Pan, James R. Foulds
The increasing use of Artificial Intelligence (AI) in critical societal domains has amplified concerns about fairness, particularly regarding unequal treatment across sensitive att…
LLM-based Corroborating and Refuting Evidence Retrieval for Scientific Claim Verification
Siyuan Wang, James R. Foulds, Md Osman Gani +1
In this paper, we introduce CIBER (Claim Investigation Based on Evidence Retrieval), an extension of the Retrieval-Augmented Generation (RAG) framework designed to identify corrobo…
Can Generative AI be Egalitarian?
Philip Feldman, James R. Foulds, Shimei Pan
The recent explosion of "foundation" generative AI models has been built upon the extensive extraction of value from online sources, often without corresponding reciprocation. This…
RAGged Edges: The Double-Edged Sword of Retrieval-Augmented Chatbots
Philip Feldman, James R. Foulds, Shimei Pan
Large language models (LLMs) like ChatGPT demonstrate the remarkable progress of artificial intelligence. However, their tendency to hallucinate -- generate plausible but false inf…