Papers by Syed Zawad

1 papers
SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging (2026.findings-acl)

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Challenge: Recent studies show that fine-tuning can erode safety alignment, causing LLMs to respond to harmful or unethical prompts.
Approach: They propose a lightweight framework that restores safety while maintaining downstream performance.
Outcome: The proposed framework reduces harmful outputs compared to other defenses, with negligible impact on utility.

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