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Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Zhao, Andrew, Ghosh, Reshmi, Carvalho, Vitor, Lawton, Emily, Hines, Keegan, Huang, Gao, Stokes, Jack W.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Computation and Language Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

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