mlsanityData to 14 Oct 2026

Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competition

arXiv 2305.06934 ↗First posted 10 May 2023cs.SE cs.AI cs.CLcited by 5

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Abstract (arXiv)

Since the release of ChatGPT, numerous studies have highlighted the remarkable performance of ChatGPT, which often rivals or even surpasses human capabilities in various tasks and domains. However, this paper presents a contrasting perspective by demonstrating an instance where human performance excels in typical tasks suited for ChatGPT, specifically in the domain of computer programming. We utilize the IEEExtreme Challenge competition as a benchmark, a prestigious, annual international programming contest encompassing a wide range of problems with different complexities. To conduct a thorough evaluation, we selected and executed a diverse set of 102 challenges, drawn from five distinct IEEExtreme editions, using three major programming languages: Python, Java, and C++. Our empirical analysis provides evidence that contrary to popular belief, human programmers maintain a competitive edge over ChatGPT in certain aspects of problem-solving within the programming context. In fact, we found that the average score obtained by ChatGPT on the set of IEEExtreme programming problems is 3.9 to 5.8 times lower than the average human score, depending on the programming language. This paper elaborates on these findings, offering critical insights into the limitations and potential areas of improvement for AI-based language models like ChatGPT.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 18 of its 51 references that are in the map. First posted on arXiv 10 May 2023.

Builds on

18 of 51 references.

References · 18

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2023A Survey of Large Language Modelscited by 2,576
  3. 2023BloombergGPT: A Large Language Model for Financecited by 939
  4. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
  5. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 488
  6. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 481
  7. 2023Mathematical Capabilities of ChatGPTcited by 268
  8. 2023Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4cited by 202
  9. 2023Regulating ChatGPT and other Large Generative AI Modelscited by 104
  10. 2023Is ChatGPT the Ultimate Programming Assistant -- How far is it?cited by 76
  11. 2023Large AI Models in Health Informatics: Applications, Challenges, and the Futurecited by 61
  12. 2023ChatGPT for Programming Numerical Methodscited by 26
6 more
  1. 2023GPTutor: a ChatGPT-powered programming tool for code explanationcited by 23
  2. 2023Investigating the use of ChatGPT for the scheduling of construction projectscited by 17
  3. 2023Linguistic ambiguity analysis in ChatGPTcited by 14
  4. 2023Many bioinformatics programming tasks can be automated with ChatGPTcited by 12
  5. 2023Conversational AI-Powered Design: ChatGPT as Designer, User, and Productcited by 8
  6. 2023Exploring the Use of ChatGPT as a Tool for Learning and Assessment in Undergraduate Computer Science Curriculum: Opportunities and Challengescited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 1; 2025: 0; 2026: 1.

5 papers.