{"as_of":"2026-08-10T06:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:15ad617ff4a6f2fa7ecf166f7a276b4de222d67c063c5fdf2b83cf5bcab3e6ec","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T16:40:11.059123Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-29T08:13:15.042714Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-08-08T16:40:11.059123Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06132","last_updated":"2025-02-10T03:46:39Z","snapshot_observed_at":"2026-08-08T16:35:50.176969Z","submitted_at":"2025-02-10T03:46:39Z","title":"Enhancing Document Key Information Localization Through Data Augmentation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-08T16:40:11.059123Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2502.06132"},"observation_digest":"sha256:320fe7f263516af2dec734c12b549413ba14296e66912e1760e585671c69243f","observation_id":"2ada8776-87d8-45c9-8cb3-af5a019af1f4","resolution":{"observed_at":"2026-08-08T16:40:11.059123Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-08-07T11:49:08.346682Z","title":"Mvqa: A dataset for multimodal information retrieval in pdf- based visual question answering.arXiv preprint arXiv:2404.12720,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01388","last_updated":"2025-06-02T07:28:28Z","snapshot_observed_at":"2026-08-10T05:59:00.365430Z","submitted_at":"2025-06-02T07:28:28Z","title":"VRD-IU: Lessons from Visually Rich Document Intelligence and Understanding","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:08.346682Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2506.01388"},"observation_digest":"sha256:0f7e35afdbc874cd90696876185df2249682671de96f4925599baa1fef487cd6","observation_id":"11227b6e-6f49-4fa6-9d1c-ed6ce3a5b060","resolution":{"observed_at":"2026-08-07T11:49:08.346682Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-08-04T20:28:56.764648Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09731","last_updated":"2025-09-10T13:02:29Z","snapshot_observed_at":"2026-08-04T20:28:42.834716Z","submitted_at":"2025-09-10T13:02:29Z","title":"Benchmarking Vision-Language Models on Chinese Ancient Documents: From OCR to Knowledge Reasoning","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T20:28:56.764648Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2509.09731"},"observation_digest":"sha256:d964f51928486e583acbeb7234c02186fe78355b70bfa906d61019177e25ba06","observation_id":"0f233e32-b037-4401-a55e-61e8655d5b7d","resolution":{"observed_at":"2026-08-04T20:28:56.764648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2404.12720","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-06-29T08:13:15.042714Z","title":"MVQA: A dataset for multimodal infor- mation retrieval in pdf-based visual question answering","venue":null,"work_id":"69a43883-61de-4f0a-8483-7584a5a83c75","year":2024},"citing_paper":{"arxiv_id":"2604.12812","last_updated":"2026-05-11T03:47:15Z","snapshot_observed_at":"2026-07-06T23:00:56.449281Z","submitted_at":"2026-04-14T14:39:26Z","title":"DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding","version":4},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T16:16:58.889065Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2604.12812"},"observation_digest":"sha256:b9588c87348594fb9732bc18bfc6bfbd07efe13e6d36b4090b83c0499d4be8e2","observation_id":"8ea5a4ee-9f61-46ee-ad81-fdafa8b38b60","resolution":{"observed_at":"2026-05-11T09:05:58.491401Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2404.12720","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-06-29T08:13:15.042714Z","title":"MVQA: A dataset for multimodal infor- mation retrieval in pdf-based visual question answering","venue":null,"work_id":"69a43883-61de-4f0a-8483-7584a5a83c75","year":2024},"citing_paper":{"arxiv_id":"2604.12812","last_updated":"2026-05-11T03:47:15Z","snapshot_observed_at":"2026-07-06T23:00:56.449281Z","submitted_at":"2026-04-14T14:39:26Z","title":"DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding","version":5},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-12T04:17:55.318813Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2604.12812"},"observation_digest":"sha256:ba5b7b2521669098827e64b82f4ddd4295cf4b19977681836e4df91758492083","observation_id":"283ec2f1-5f71-4a8a-9021-a12dce7a11ae","resolution":{"observed_at":"2026-05-12T06:26:24.407871Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2404.12720","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-06-29T08:13:15.042714Z","title":"MVQA: A dataset for multimodal infor- mation retrieval in pdf-based visual question answering","venue":null,"work_id":"69a43883-61de-4f0a-8483-7584a5a83c75","year":2024},"citing_paper":{"arxiv_id":"2604.23276","last_updated":"2026-04-25T12:40:13Z","snapshot_observed_at":"2026-07-06T23:09:34.300163Z","submitted_at":"2026-04-25T12:40:13Z","title":"Lightweight and Production-Ready PDF Visual Element Parsing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T08:31:44.430067Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2604.23276"},"observation_digest":"sha256:0798108f1745b1a1541a20b42a40ec6cfc5e04fb26fcd3b977d163820618bc3a","observation_id":"078c664f-980d-4fb2-9d3d-39ca10e0cd31","resolution":{"observed_at":"2026-05-11T20:36:09.148986Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2404.12720","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-06-29T08:13:15.042714Z","title":"MVQA: A dataset for multimodal infor- mation retrieval in pdf-based visual question answering","venue":null,"work_id":"69a43883-61de-4f0a-8483-7584a5a83c75","year":2024},"citing_paper":{"arxiv_id":"2605.30027","last_updated":"2026-05-28T14:50:53Z","snapshot_observed_at":"2026-08-06T11:47:39.586448Z","submitted_at":"2026-05-28T14:50:53Z","title":"DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-29T08:09:41.068000Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2605.30027"},"observation_digest":"sha256:2e52f0fa868ce74cbf109d96fc3e101273cdeaab2fb18f74c5a9616c18a8c3ee","observation_id":"3339602c-1ccd-484f-8fed-3b001e845583","resolution":{"observed_at":"2026-06-29T08:13:15.044494Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12720","snapshot_observed_at":"2026-08-02T14:55:34.545662Z","title":"arXiv preprint arXiv:2404.12720 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16203","last_updated":"2026-05-05T10:59:34Z","snapshot_observed_at":"2026-08-04T21:09:24.743822Z","submitted_at":"2026-05-05T10:59:34Z","title":"DocOCR-Eval: A Correction-Based Framework for OCR Tool Selection Without Ground Truth","version":1},"reference_index":121,"source":"arxiv_source","source_observed_at":"2026-08-02T14:55:34.545662Z"},"links":{"cited_paper":"/paper/2404.12720","citing_paper":"/paper/2607.16203"},"observation_digest":"sha256:e6d9b4eb4efb3749c9e1883b79d1f0880ffa87ee9f74603f34958de6912f49e5","observation_id":"7a4c4363-aebd-46d1-9fa1-a2571c95fa34","resolution":{"observed_at":"2026-08-02T14:55:34.545662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.12720/citation-record","integrity":"/paper/2404.12720/integrity","json":"/paper/2404.12720/citation-record.json","paper":"/paper/2404.12720"},"outbound":[],"paper":{"arxiv_id":"2404.12720","last_updated":"2024-04-19T09:00:05Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T18:02:36.759308Z","submitted_at":"2024-04-19T09:00:05Z","title":"PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.12720."}