Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics

1 code implementation • 4 Apr 2024 • Fangru Lin, Daniel Altshuler, Janet B. Pierrehumbert

In this study, we probe different families of Large Language Models such as GPT-4 for their knowledge of the lexical semantics of scalar adjectives and one specific aspect of their pragmatics, namely scalar diversity.

GPT-4 Implicatures

Graph-enhanced Large Language Models in Asynchronous Plan Reasoning

no code implementations • 5 Feb 2024 • Fangru Lin, Emanuele La Malfa, Valentin Hofmann, Elle Michelle Yang, Anthony Cohn, Janet B. Pierrehumbert

Reasoning about asynchronous plans is challenging since it requires sequential and parallel planning to optimize time costs.

GPT-4 Llama

Code Simulation Challenges for Large Language Models

no code implementations • 17 Jan 2024 • Emanuele La Malfa, Christoph Weinhuber, Orazio Torre, Fangru Lin, Anthony Cohn, Nigel Shadbolt, Michael Wooldridge

We investigate the extent to which Large Language Models (LLMs) can simulate the execution of computer code and algorithms.