32 citations · 64 across the 12 of their papers we have counts for
7 papers · 1 filter
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…
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…
Learning to Draw ASCII Improves Spatial Reasoning in Language Models
Shiyuan Huang, Li Liu, Jincheng He +1
When faced with complex spatial problems, humans naturally sketch layouts to organize their thinking, and the act of drawing further sharpens their understanding. In this work, we…
Anticipatory Thinking Challenges in Open Worlds: Risk Management
Adam Amos-Binks, Dustin Dannenhauer, Leilani H. Gilpin
Anticipatory thinking drives our ability to manage risk - identification and mitigation - in everyday life, from bringing an umbrella when it might rain to buying car insurance. As…
Establishing Meta-Decision-Making for AI: An Ontology of Relevance, Representation and Reasoning
Cosmin Badea, Leilani Gilpin
We propose an ontology of building decision-making systems, with the aim of establishing Meta-Decision-Making for Artificial Intelligence (AI), improving autonomy, and creating a f…
Explaining Explanations to Society
Leilani H. Gilpin, Cecilia Testart, Nathaniel Fruchter +1
There is a disconnect between explanatory artificial intelligence (XAI) methods and the types of explanations that are useful for and demanded by society (policy makers, government…
Explaining Explanations: An Overview of Interpretability of Machine Learning
Leilani H. Gilpin, David Bau, Ben Z. Yuan +3
There has recently been a surge of work in explanatory artificial intelligence (XAI). This research area tackles the important problem that complex machines and algorithms often ca…