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.AI2026
Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning
Olivia Peiyu Wang, Leilani H. Gilpin
The growing adoption of large language models in legal practice brings both significant promise and serious risk. Legal professionals stand to benefit from AI that can reason over…
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…