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AAAI 2026 杰出论文 | 同济&微软等提出 LLM2CLIP:补足 CLIP 难以处理长 ...
过去我们试图通过堆视觉数据来提升 CLIP,但 LLM2CLIP 证明了,通过引入一个已经“读过万卷书”的 LLM,并辅以少量的、高质量的描述数据,就能让视觉表征产生质的飞跃。这种“低成本、高收益”的方案,很可能会成为未来多模态预训练的新范式。 目前 ...
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