Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

23 April 2024

Bo Du

Papers citing "Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems"

7 / 7 papers shown

Title
PhD Knowledge Not Required: A Reasoning Challenge for Large Language Models C. Anderson Joydeep Biswas Aleksander Boruch-Gruszecki Federico Cassano Molly Q. Feldman Joydeep Biswas Francesca Lucchetti Zixuan Wu Arjun Guha ReLM ELM LRM 37 3 0 03 Feb 2025
Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted Narratives Xinliang Frederick Zhang Nick Beauchamp Lu Wang LRM AI4CE 19 3 0 07 Oct 2024
Complexity-Based Prompting for Multi-Step Reasoning Yao Fu Hao-Chun Peng Ashish Sabharwal Peter Clark Tushar Khot ReLM LRM 152 298 0 03 Oct 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 2,712 0 24 May 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 301 11,730 0 04 Mar 2022
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies Mor Geva Daniel Khashabi Elad Segal Tushar Khot Dan Roth Jonathan Berant RALM 242 460 0 06 Jan 2021