🔗 Who cites «A Categorical Archive of ChatGPT Failures»

50 papers of our library cite it (of the 141,840 whose bibliographies we read) · 9 with a page here, the most cited first · ← back to «A Categorical Archive of ChatGPT Failures»

1. Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language ModelsarXiv:2304.01852 · Meta-Radiology (2023)100,017Yiheng Liu, Tianle Han, Siyuan Ma, et al.2023 · 938 citations
2. ChatGPT: Jack of all trades, master of nonearXiv:2302.10724 · Information Fusion 101,861 (2023)Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al.2023 · 865 citations
   Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 378 citations
3. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 300 citations
4. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 246 citations
5. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 226 citations
6. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 220 citations
   A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
7. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 150 citations

41 more papers of our library cite it; they have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/borji-2023-categorical-archive-chatgpt-failures/cited-by/