DocPC: Document-Level Visual Retrieval via Representative Page Composition

• URL: http://arxiv.org/abs/2608.25434v3
• Date: Fri, 28 Aug 2026 07:33:35 GMT
• Title: DocPC: Document-Level Visual Retrieval via Representative Page Composition
• Abstract summary: We propose DocPC, a document-level visual retrieval framework based on Representative Page Composition.<n>We combine multi-positive contrastive learning with sparsely scheduled listwise optimization to handle multi-positive supervision prevalent at the document level.<n> DocPC-ColQwen achieves NDCG@5 of 44.09 on DocViRe, outperforming the strongest page-level baseline at 38.91 while reducing storage by 10.1x.
• Score: 18.502834715003928
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Visual document retrieval has advanced by encoding page screenshots with vision-language models, bypassing OCR pipelines. However, existing methods remain page-centric, misaligned with real-world scenarios requiring complete document retrieval. A naive page-then-document aggregation suffers from linear indexing cost and degraded retrieval when relevance spans multiple pages. We propose DocPC, a document-level visual retrieval framework based on Representative Page Composition: selecting representative pages and composing them into a single grid image for document-level indexing, reducing indexed images, vectors, and storage by 10.1x and end-to-end indexing time by roughly 7.7x. To handle multi-positive supervision prevalent at the document level, we combine multi-positive contrastive learning with sparsely scheduled listwise optimization. We also introduce DocViRe, a benchmark with multi-positive relevance annotations. DocPC-ColQwen achieves NDCG@5 of 44.09 on DocViRe, outperforming the strongest page-level baseline at 38.91 while reducing storage by 10.1x. Code is available at https://anonymous.4open.science/r/DocPC-Document-Level-Visual-Retrieval-via-Representative-Page-Comp osition-1D52. Data is available at https://huggingface.co/datasets/anonymous-7219/docpc.

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