SAFT (Safety-preserving Adaptation via Fine-tuning Transfer), a safety-preserving adaptation framework that decouples task learning from alignment preservation by learning a safety-guided task update on the paired pretrained base model, rectifying task gradients to avoid conflicting directions with respect to a safety...
Zhiwen Ruan, Yan Yang, Zhuocheng Liang et al.· Proceedings of the 32nd ACM...· 0 citations
AlignDiff, a preference data filtering framework driven by intrinsic model signals, first identifies samples with clear preferences using both positive and inverse signals, then prioritizes the more challenging samples based on the average negative log-likelihood gap, encouraging the model to learn richer information f...
Vision-Free Adaptation (VFA) is proposed, a framework that decouples multilingual language enhancement from visual alignment by composing complementary task vectors over a shared LLM backbone.
Yixia Li, Yaqing Shi, Zhiwen Ruan et al.· Annual Meeting of the Associ...· 0 citations
SAFT (Safety-preserving Adaptation via Fine-tuning Transfer), a safety-preserving adaptation framework that decouples task learning from alignment preservation by learning a safety-guided task update on the paired pretrained base model, rectifying task gradients to avoid conflicting directions with respect to a safety...
Zhiwen Ruan, Yan Yang, Zhuocheng Liang et al.· Proceedings of the 32nd ACM...· 0 citations
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