mlsanityData to 7 Oct 2026

ChatGPT-Crawler: Find out if ChatGPT really knows what it's talking about

arXiv 2304.03325 ↗First posted 6 Apr 2023cs.CL cs.IR cs.LGcited by 3

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Abstract (arXiv)

Large language models have gained considerable interest for their impressive performance on various tasks. Among these models, ChatGPT developed by OpenAI has become extremely popular among early adopters who even regard it as a disruptive technology in many fields like customer service, education, healthcare, and finance. It is essential to comprehend the opinions of these initial users as it can provide valuable insights into the potential strengths, weaknesses, and success or failure of the technology in different areas. This research examines the responses generated by ChatGPT from different Conversational QA corpora. The study employed BERT similarity scores to compare these responses with correct answers and obtain Natural Language Inference(NLI) labels. Evaluation scores were also computed and compared to determine the overall performance of GPT-3 & GPT-4. Additionally, the study identified instances where ChatGPT provided incorrect answers to questions, providing insights into areas where the model may be prone to error.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 17 of its 35 references that are in the map. First posted on arXiv 6 Apr 2023.

Builds on

17 of 35 references.

References · 17

  1. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  2. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 719
  3. 2018CoQA: A Conversational Question Answering Challengecited by 674
  4. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 486
  5. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
  6. 2023Regulating ChatGPT and other Large Generative AI Modelscited by 102
  7. 2022ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reportscited by 100
  8. 2022ChatGPT: The End of Online Exam Integrity?cited by 88
  9. 2023ChatGPT is not all you need. A State of the Art Review of large Generative AI modelscited by 85
  10. 2023Can ChatGPT Assess Human Personalities? A General Evaluation Frameworkcited by 69
  11. 2021DialFact: A Benchmark for Fact-Checking in Dialoguecited by 62
  12. 2023Will ChatGPT get you caught? Rethinking of Plagiarism Detectioncited by 41
5 more
  1. 2021FaVIQ: FAct Verification from Information-seeking Questionscited by 36
  2. 2022"I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Datacited by 32
  3. 2023Towards Human-Bot Collaborative Software Architecting with ChatGPTcited by 31
  4. 2023Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labelscited by 12
  5. 2023UZH_CLyp at SemEval-2023 Task 9: Head-First Fine-Tuning and ChatGPT Data Generation for Cross-Lingual Learning in Tweet Intimacy Predictioncited by 8

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Cited by year

Citing papers per year: 2023: 2; 2024: 1.

3 papers.