作者位次 #2/5ICLR 2026Poster· Social Aspects / Fairness, Equity, Justice and Safety
Any-Depth Alignment: Unlocking Innate Safety Alignment of LLMs to Any-Depth
Jiawei Zhang · Andrew Estornell · David Baek · Bo Li · Xiaojun Xu
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Jiawei Zhang · Andrew Estornell · David Baek · Bo Li · Xiaojun Xu
Zimu Jia · Mingjie Xu · Andrew Estornell · Jiaheng Wei
The efficacy of Large Vision-Language Models (LVLMs) is critically dependent on the quality of their training data, requiring a precise balance between visual fidelity and instruction-following capability. Existing datasets, however, are plagued by inconsistent quality, and current data filtering...