{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:DC2VUGFUR4UMGNJVULYQ5PXN6K","short_pith_number":"pith:DC2VUGFU","schema_version":"1.0","canonical_sha256":"18b55a18b48f28c33535a2f10ebeedf2aae59768fd3877bc8b15afde69e54b86","source":{"kind":"arxiv","id":"2606.08979","version":1},"attestation_state":"computed","paper":{"title":"EviProp: Seeded Relevance Diffusion on Chunk-Page Graphs for Long Multimodal Document Retrieval","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Botian Shi, Fuke Shen, Guohang Yan, Hongwei Zhang, Pinlong Cai, Ruicheng Zhu, Tongquan Wei, Xiaoman Wang, Yue Zhang, Zehui Ling","submitted_at":"2026-06-08T03:25:20Z","abstract_excerpt":"Retrieving evidence pages from visually rich long documents is a key challenge in document question answering. Existing page-level visual retrievers operate under an independent matching paradigm: each page is scored in isolation based on query-page similarity. This paradigm can under-rank evidence pages whose signals are localized in fine-grained chunks or depend on document-internal associations. We propose EviProp, a retrieval method that recovers such pages via seeded relevance diffusion. EviProp models each document as a multimodal Chunk-Page graph with hierarchical, sequential, and simil"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.08979","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-06-08T03:25:20Z","cross_cats_sorted":[],"title_canon_sha256":"86fa1a395121023bec2f0468437e78847e759a581dee143b1f79a25ba5349023","abstract_canon_sha256":"11f1e6b92217125f43524a8ac0d4d586abc9cfcd459cadca796fef3b440f8827"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:07:51.487901Z","signature_b64":"U3KCMaGRdPydS0FfijHNDA6IXCve4nxjy61qEuY05taYXrV57Dn2D3sNCNG4Fteq9NWU9fcahonz7pQPUGmWDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18b55a18b48f28c33535a2f10ebeedf2aae59768fd3877bc8b15afde69e54b86","last_reissued_at":"2026-06-09T02:07:51.487144Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:07:51.487144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EviProp: Seeded Relevance Diffusion on Chunk-Page Graphs for Long Multimodal Document Retrieval","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Botian Shi, Fuke Shen, Guohang Yan, Hongwei Zhang, Pinlong Cai, Ruicheng Zhu, Tongquan Wei, Xiaoman Wang, Yue Zhang, Zehui Ling","submitted_at":"2026-06-08T03:25:20Z","abstract_excerpt":"Retrieving evidence pages from visually rich long documents is a key challenge in document question answering. Existing page-level visual retrievers operate under an independent matching paradigm: each page is scored in isolation based on query-page similarity. This paradigm can under-rank evidence pages whose signals are localized in fine-grained chunks or depend on document-internal associations. We propose EviProp, a retrieval method that recovers such pages via seeded relevance diffusion. EviProp models each document as a multimodal Chunk-Page graph with hierarchical, sequential, and simil"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08979","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.08979/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.08979","created_at":"2026-06-09T02:07:51.487266+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.08979v1","created_at":"2026-06-09T02:07:51.487266+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08979","created_at":"2026-06-09T02:07:51.487266+00:00"},{"alias_kind":"pith_short_12","alias_value":"DC2VUGFUR4UM","created_at":"2026-06-09T02:07:51.487266+00:00"},{"alias_kind":"pith_short_16","alias_value":"DC2VUGFUR4UMGNJV","created_at":"2026-06-09T02:07:51.487266+00:00"},{"alias_kind":"pith_short_8","alias_value":"DC2VUGFU","created_at":"2026-06-09T02:07:51.487266+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K","json":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K.json","graph_json":"https://pith.science/api/pith-number/DC2VUGFUR4UMGNJVULYQ5PXN6K/graph.json","events_json":"https://pith.science/api/pith-number/DC2VUGFUR4UMGNJVULYQ5PXN6K/events.json","paper":"https://pith.science/paper/DC2VUGFU"},"agent_actions":{"view_html":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K","download_json":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K.json","view_paper":"https://pith.science/paper/DC2VUGFU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.08979&json=true","fetch_graph":"https://pith.science/api/pith-number/DC2VUGFUR4UMGNJVULYQ5PXN6K/graph.json","fetch_events":"https://pith.science/api/pith-number/DC2VUGFUR4UMGNJVULYQ5PXN6K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K/action/storage_attestation","attest_author":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K/action/author_attestation","sign_citation":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K/action/citation_signature","submit_replication":"https://pith.science/pith/DC2VUGFUR4UMGNJVULYQ5PXN6K/action/replication_record"}},"created_at":"2026-06-09T02:07:51.487266+00:00","updated_at":"2026-06-09T02:07:51.487266+00:00"}