Author

Yongqi Zhang

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Preprint Aug 2026

RePair: Turning Retrieval Failures into Counterfactual Hard Pairs

Vision-language retrieval with CLIP-style dual encoders achieves strong cross-modal performance, yet practical accuracy often hinges on localized semantic distinctions where top-ranked near misses differ from the true match by a single critical detail. Hard-sample mining can select confusable candidates but cannot cons...

Siyi Liu, Xiao-Rong Zhu, En-Jun Du et al. · 0 citations

Preprint Sep 2026

From Saliency to Discriminability: Rank-Preserving Visual Token Pruning for VLM Rerankers

Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning essential for practical deployment. Existing pruning methods retain tokens by attention saliency, yet we show that saliency is systematically misaligned with ranking contrib...

Siyi Liu, Han-Jun Yang, Chen-Chen Zhang et al. · 0 citations

Preprint Aug 2026

EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking

Real-world image search queries are multimodal and compositional: ``find this shirt in pink''specifies an entity to retain, an attribute to modify, and context to ignore. Yet existing re-rankers either compress such multifaceted relevance into an opaque embedding or rely on free-form chain-of-thought that easily omits...

Enjun Du, Siyi Liu, Zi-Rong Chen et al. · 1 citation