title: An Empirical Study on Challenging Math Problem Solving with GPT-4
summary: Employing Large Language Models (LLMs) to address mathematical problems is an
  intriguing research endeavor, considering the abundance of math problems
  expressed in natural language across numerous science and engineering fields.
  While several prior works have investigated solving elementary mathematics
  using LLMs, this work explores the frontier of using GPT-4 for solving more
  complex and challenging math problems. We evaluate various ways of using GPT-4.
  Some of them are adapted from existing work, and one is \MathChat, a
  conversational problem-solving framework newly proposed in this work. We
  perform the evaluation on difficult high school competition problems from the
  MATH dataset, which shows the advantage of the proposed conversational
  approach.
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paper_authors.fullname: Yiran Wu
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paper_authors.user: kevinwyr
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paper_authors.name: Feiran Jia
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paper_authors.fullname: Feiran Jia
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paper_authors.user: jtongxin
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paper_authors.name: Shaokun Zhang
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paper_authors.fullname: shaokun zhang
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paper_authors.user: Shaokunkun
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paper_authors.name: Qingyun Wu
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paper_authors.fullname: Qingyun Wu
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paper_authors.user: qingyun-wu
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paper_authors.name: Hangyu Li
paper_authors._id: 647d3dab83cdb93baf76ede1
paper_authors.name: Erkang Zhu
paper_authors._id: 647d3dab83cdb93baf76ede2
paper_authors.name: Yue Wang
paper_authors._id: 647d3dab83cdb93baf76ede3
paper_authors.name: Yin Tat Lee
paper_authors._id: 647d3dab83cdb93baf76ede4
paper_authors.name: Richard Peng
paper_authors._id: 647d3dab83cdb93baf76ede5
paper_authors.name: Chi Wang
paper_authors.status: claimed_verified
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paper_authors._id: 640baf807047b6c332a912e1
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paper_authors.fullname: Chi Wang
paper_authors.type: user
paper_authors.user: sonichi
paper_title: An Empirical Study on Challenging Math Problem Solving with GPT-4
paper_summary: Employing Large Language Models (LLMs) to address mathematical problems is an
  intriguing research endeavor, considering the abundance of math problems
  expressed in natural language across numerous science and engineering fields.
  While several prior works have investigated solving elementary mathematics
  using LLMs, this work explores the frontier of using GPT-4 for solving more
  complex and challenging math problems. We evaluate various ways of using GPT-4.
  Some of them are adapted from existing work, and one is \MathChat, a
  conversational problem-solving framework newly proposed in this work. We
  perform the evaluation on difficult high school competition problems from the
  MATH dataset, which shows the advantage of the proposed conversational
  approach.
paper_ai_summary: A study evaluates the use of GPT-4 for solving complex mathematical problems using various methods, including a new conversational framework called MathChat, demonstrating its effectiveness on challenging high school competition problems.
paper_ai_keywords: Large Language Models LLMs GPT-4 MathChat conversational problem-solving framework MATH dataset