Solving complex problems with large language models

Amphi Kahn

One of the great promises that people connect with LLMs is that they can make complex problem-solving with computers accessible to lay users. Unlike traditional symbolic solvers (e.g. for planning or linear programming), LLMs accept natural-language input and require no expert training; unlike earlier task-oriented dialogue systems, they can be applied across arbitrary domains.

In my talk, I will explore the degree to which LLMs are already fulfilling this promise. I will present recent work on whether current LLMs « reason » or « recite », discuss the role of symbolic representations in LLM-based problem-solving, and offer some thoughts on trustworthy problem-solving with LLMs.

More information on Loria’s colloqium’s webpage