To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices

Sean McGregor, Allyson Ettinger, Nick Judd, Paul Albee, Liwei Jiang, Kavel Rao, William H. Smith, Shayne Longpre, Avijit Ghosh, Christopher Fiorelli, Michelle Hoang, Sven Cattell, Nouha Dziri

AAAI 2025 pp. 28938-28945

doi:10.1609/AAAI.V39I28.35162 /aaai/2025/mcgregor2025aaai-err/

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Cite

Text

McGregor et al. "To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35162

Markdown

[McGregor et al. "To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/mcgregor2025aaai-err/) doi:10.1609/AAAI.V39I28.35162

BibTeX

@inproceedings{mcgregor2025aaai-err,
  title     = {{To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices}},
  author    = {McGregor, Sean and Ettinger, Allyson and Judd, Nick and Albee, Paul and Jiang, Liwei and Rao, Kavel and Smith, William H. and Longpre, Shayne and Ghosh, Avijit and Fiorelli, Christopher and Hoang, Michelle and Cattell, Sven and Dziri, Nouha},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {28938-28945},
  doi       = {10.1609/AAAI.V39I28.35162},
  url       = {https://mlanthology.org/aaai/2025/mcgregor2025aaai-err/}
}