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Sheng Zhong

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#artificial intelligence Preprint Jul 2026

Lens: Bringing the Right Semantic Perspective into Focus for Training-Free Multimodal Representation Learning

Lens is a training-free framework that makes representation readout task-directed, and achieves an overall Precision@1 of 63.9 across all 36 MMEB datasets, outperforming the closest same-backbone training-free embedding baseline by 10.2 points.

Xin-Ran Liu, Shou-Qian Shi, Yi-Xian Chen et al. · 0 citations
Jul 2026

TraceCLIP: Recovering Local Semantics from Patch-to-CLS Contributions

Dense vision-language understanding, including object localization, region recognition, and open-vocabulary semantic segmentation, requires associating language concepts with spatially grounded visual regions. CLIP provides a strong foundation for these tasks by learning a shared image-text embedding space from large-s...

Xinran Liu, Shouqian Shi, Yutong Chen et al. · 0 citations

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