← all papers · overview

In-context Symbolic Regression: Leveraging Large Language Models For Function Discovery

Abstract

State of the art Symbolic Regression (SR) methods currently build specialized models, while the application of Large Language Models (LLMs) remains largely unexplored. In this work, we introduce the first comprehensive framework that utilizes LLMs for the task of SR. We propose In-Context Symbolic Regression (ICSR), an SR method which iteratively refines a functional form with an LLM and determine

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).