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cs.CL2025
Hallucinate Less by Thinking More: Aspect-Based Causal Abstention for Large Language Models
Vy Nguyen, Ziqi Xu, Jeffrey Chan +3
Large Language Models (LLMs) often produce fluent but factually incorrect responses, a phenomenon known as hallucination. Abstention, where the model chooses not to answer and inst…
cs.CL2025
An Empirical Study of the Role of Incompleteness and Ambiguity in Interactions with Large Language Models
Riya Naik, Ashwin Srinivasan, Estrid He +1
Natural language as a medium for human-computer interaction has long been anticipated, has been undergoing a sea-change with the advent of Large Language Models (LLMs) with startli…
cs.CL2025
Deep Contrastive Unlearning for Language Models
Estrid He, Tabinda Sarwar, Ibrahim Khalil +2
The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual data and generating human-like language…