Papers by Jinyuan Xu

2 papers
Attention Consistency for LLMs Explanation (2025.findings-emnlp)

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Challenge: Existing interpretability methods face limitations such as low resolution and high computational cost.
Approach: They propose a multi-layer attention consistency score to estimate the importance of input tokens in large language models.
Outcome: The proposed heuristic achieves a favorable trade-off between interpretability quality and computational efficiency .
SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding (2024.acl-long)

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Challenge: Despite advances in large language models, they face substantial challenges in terms of safety.
Approach: They develop a safety-aware decoding strategy for large language models to defend against jailbreak attacks.
Outcome: The proposed strategy outperforms six defense methods against jailbreak attacks on five LLMs.

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