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cs.CR2026
Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks
John T. Halloran, Noopur S. Bhatt
Large language models (LLMs) are highly susceptible to backdoor attacks (BAs), wherein training samples are poisoned using trigger-based harmful content. Furthermore, existing defe…
cs.CR2026
Understanding the Effects of Safety Unalignment on Large Language Models
John T. Halloran
Safety alignment has become a critical step to ensure LLMs refuse harmful requests while providing helpful and harmless responses. However, despite the ubiquity of safety alignment…