3 citations · 8 across the 10 of their papers we have counts for
8 papers · 1 filter
FlexVDR: Learning to Allocate Matryoshka Representation Budgets for Visual Document Retrieval
Haowen Xiang, Yibo Yan, Xin Zou +4
Visual document retrieval relies on rich multi-vector representations to capture fine-grained evidence in document pages, but encoding and matching these representations can be com…
AnchorFold: A Focus-Then-Fold Framework via Recursive Attention Propagation for Efficient Multi-Vector Visual Document Retrieval
Haoyu Zuo, Yibo Yan, Xin Zou +4
Multi-vector vision-language retrievers enable fine-grained Visual Document Retrieval (VDR) through late interaction, but storing and scoring hundreds of visual patch embeddings pe…
MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework
Haowen Xiang, Yibo Yan, Jiahao Huo +4
Multi-vector visual document retrievers achieve strong fine-grained matching by representing each page with multiple vectors from deep Vision-Language Models (VLMs), but this desig…
Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval
Yibo Yan, Mingdong Ou, Yi Cao +5
Multi-vector models dominate Visual Document Retrieval (VDR) due to their fine-grained matching capabilities, but their high storage and computational costs present a major barrier…
Beyond the Grid: Layout-Informed Multi-Vector Retrieval with Parsed Visual Document Representations
Yibo Yan, Mingdong Ou, Yi Cao +6
Harnessing the full potential of visually-rich documents requires retrieval systems that understand not just text, but intricate layouts, a core challenge in Visual Document Retrie…
Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval
Yibo Yan, Jiahao Huo, Guanbo Feng +12
With the rapid proliferation of multimodal information, Visual Document Retrieval (VDR) has emerged as a critical frontier in bridging the gap between unstructured visually rich da…
Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework
Yibo Yan, Mingdong Ou, Yi Cao +5
Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current multimodal retrieval applicatio…
CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding
Jiahao Huo, Yu Huang, Yibo Yan +7
Although Multimodal Large Language Models (MLLMs) have shown remarkable potential in Visual Document Retrieval (VDR) through generating high-quality multi-vector embeddings, the su…