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Efficient LLM Adversarial Training via Low-Rank Defense and Circuit-Guided Surrogates
Adversarial training is one of the most effective defenses against adversarial attacks, yet the computational cost remains prohibitive at modern scales, especially for large language models (LLMs). While existing mitigation strategies, e.g., latent adversarial training (LAT), have been developed, th
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