3 papers
cs.AI2026
Know Your Limits : On the Faithfulness of LLMs as Solvers and Autoformalizers in Legal Reasoning
Olivia Peiyu Wang, Sanna Wong-Toropainen, Daneshvar Amrollahi +4
Large Language Models (LLMs) achieve strong performance on reasoning tasks, but whether this reflects faithful logical inference or heuristic approximation remains unclear. We stud…
cs.HC2025
Offscript: Automated Auditing of Instruction Adherence in LLMs
Nicholas Clark, Ryan Bai, Tanu Mitra
Large Language Models (LLMs) and generative search systems are increasingly used for information seeking by diverse populations with varying preferences for knowledge sourcing and…
cs.AI2025
Follow My Lead: Logical Fallacy Classification with Knowledge-Augmented LLMs
Olivia Peiyu Wang, Tashvi Bansal, Ryan Bai +2
Large Language Models (LLMs) suffer from critical reasoning gaps, including a tendency to hallucinate and poor accuracy in classifying logical fallacies. This limitation stems from…