A Personalised Learning Tool for Physics Undergraduate Students Built On
a Large Language Model for Symbolic Regression

A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression

17 June 2024

Jonathan Sze Choong Low

Stephane Bressan

Papers citing "A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression"

7 / 7 papers shown

Title
Prompting Large Language Models With the Socratic Method Edward Y. Chang LRM ELM 51 48 0 17 Feb 2023
Complexity-Based Prompting for Multi-Step Reasoning Yao Fu Hao-Chun Peng Ashish Sabharwal Peter Clark Tushar Khot ReLM LRM 162 414 0 03 Oct 2022
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge Liron Simon Keren A. Liberzon Teddy Lazebnik 25 81 0 13 Sep 2022
Symbolic Regression is NP-hard M. Virgolin S. Pissis 64 61 0 03 Jul 2022
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations Jaehun Jung Lianhui Qin Sean Welleck Faeze Brahman Chandra Bhagavatula Ronan Le Bras Yejin Choi ReLM LRM 223 190 0 24 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 367 8,495 0 28 Jan 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 279 1,121 0 18 Apr 2021