{"as_of":"2026-08-08T15:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:da65370a2e2f00c90456cb97a59509f9668ff1454144c7c48001d9c28ca93e13","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:01:13.802547Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T11:01:15.324347Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.17904","last_updated":"2024-11-08T10:45:12Z","snapshot_observed_at":"2026-07-06T17:23:10.017122Z","submitted_at":"2024-01-31T15:10:29Z","title":"Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation","version":2},"cited_work":{"arxiv_id":"2401.17904","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.17904","snapshot_observed_at":"2026-08-07T11:01:15.324347Z","title":"Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation","venue":"cs.CV","work_id":"2e9f273a-197f-45c3-bda3-0163c1ab11c5","year":2024},"citing_paper":{"arxiv_id":"2506.03799","last_updated":"2025-06-04T10:06:32Z","snapshot_observed_at":"2026-08-08T13:03:29.824359Z","submitted_at":"2025-06-04T10:06:32Z","title":"ConText: Driving In-context Learning for Text Removal and Segmentation","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-07T11:01:13.802547Z"},"links":{"cited_paper":"/paper/2401.17904","citing_paper":"/paper/2506.03799"},"observation_digest":"sha256:45ea0f5f19e25befcb458329c00205369501a52b213c4393153ebf9ef7022563","observation_id":"e1ba47f6-40a8-4491-aa84-6737154ac828","resolution":{"observed_at":"2026-08-07T11:01:15.329321Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2401.17904/citation-record","integrity":"/paper/2401.17904/integrity","json":"/paper/2401.17904/citation-record.json","paper":"/paper/2401.17904"},"outbound":[],"paper":{"arxiv_id":"2401.17904","last_updated":"2024-11-08T10:45:12Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T17:23:10.017122Z","submitted_at":"2024-01-31T15:10:29Z","title":"Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2401.17904."}