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Exploring Advanced Methodologies in Security Evaluation for LLMs (2402.17970v2)

Published 28 Feb 2024 in cs.CR

Abstract: LLMs represent an advanced evolution of earlier, simpler LLMs. They boast enhanced abilities to handle complex language patterns and generate coherent text, images, audios, and videos. Furthermore, they can be fine-tuned for specific tasks. This versatility has led to the proliferation and extensive use of numerous commercialized large models. However, the rapid expansion of LLMs has raised security and ethical concerns within the academic community. This emphasizes the need for ongoing research into security evaluation during their development and deployment. Over the past few years, a substantial body of research has been dedicated to the security evaluation of large-scale models. This article an in-depth review of the most recent advancements in this field, providing a comprehensive analysis of commonly used evaluation metrics, advanced evaluation frameworks, and the routine evaluation processes for LLMs. Furthermore, we also discuss the future directions for advancing the security evaluation of LLMs.

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Authors (5)
  1. Jun Huang (126 papers)
  2. Jiawei Zhang (529 papers)
  3. Qi Wang (560 papers)
  4. Weihong Han (1 paper)
  5. Yanchun Zhang (15 papers)