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Awesome GitHub RepositoriesAdversarial Suffix Optimization
Applying gradient descent to optimize string sequences that trigger prohibited model responses.
Distinct from Gradient Descent Algorithms: Focuses on optimizing input tokens for adversarial attack rather than updating model parameters for training.
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Awesome Adversarial Suffix Optimization GitHub Repositories
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- llm-attacks/llm-attacks
llm-attacks/llm-attacks
4,509在 GitHub 上查看This repository provides tools and methodologies for studying adversarial attacks on large language models. It focuses on understanding how carefully crafted inputs can manipulate or bypass the safety mechanisms of LLMs, enabling researchers to probe model vulnerabilities and improve their robustness. The project covers techniques for generating adversarial prompts, evaluating model responses under attack conditions, and analyzing the effectiveness of different attack strategies.
Uses coordinate gradient descent to iteratively refine token sequences that maximize adversarial response probability.
Python
