How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities

How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities Lingbo Mo author Boshi Wang author Muhao Chen author Huan Sun author 2024-06 text Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) Kevin Duh editor Helena Gomez editor Steven Bethard editor Association for Computational Linguistics Mexico City, Mexico conference publication mo-etal-2024-trustworthy 10.18653/v1/2024.naacl-long.152 https://aclanthology.org/2024.naacl-long.152/ 2024-06 2775 2792