Papers by Hasan Hammoud

1 papers
Model Merging and Safety Alignment: One Bad Model Spoils the Bunch (2024.findings-emnlp)

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Challenge: Existing methods for merging large language models often overlook safety alignment during merging, leading to misaligned models.
Approach: They propose to combine safety and domain-specific data to optimize model merging techniques . they propose to use this data to maximize model alignment .
Outcome: The proposed method allows for models that excel in both domain expertise and alignment.

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