Papers by Maithili Joshi

1 papers
SABER: Uncovering Vulnerabilities in Safety Alignment via Cross-Layer Residual Connection (2025.emnlp-main)

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Challenge: Large Language Models (LLMs) with safe-alignment training are vulnerable to jailbreak attacks, causing malicious users to generate harmful outputs.
Approach: They propose a safe-alignment jailbreak method that bypasses the middle-to-late layers of large language models by a residual connection.
Outcome: The proposed method improves by 51% over the best performing baseline GCG on HarmBench test set.

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