{"as_of":"2026-08-08T14:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:64aed7088f34e88142effd3bca91287adb005d961befabec79a7a2e9bca5d16c","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:17:16.754728Z","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":"2026-05-25T07:50:29.392204Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.10362","last_updated":"2024-06-04T08:31:15Z","snapshot_observed_at":"2026-08-03T23:06:17.930023Z","submitted_at":"2023-10-16T12:58:04Z","title":"Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10362","snapshot_observed_at":"2026-08-07T05:17:16.754728Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08326","last_updated":"2025-06-10T01:27:19Z","snapshot_observed_at":"2026-08-07T05:11:09.756792Z","submitted_at":"2025-06-10T01:27:19Z","title":"Graph Prompting for Graph Learning Models: Recent Advances and Future Directions","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:17:16.754728Z"},"links":{"cited_paper":"/paper/2310.10362","citing_paper":"/paper/2506.08326"},"observation_digest":"sha256:81b28e5d06701a42f5aeb707abb362a9f95fbb5723bce458f077d4c9c8b90118","observation_id":"e746ba79-1691-43fc-aaee-94916e57e1fd","resolution":{"observed_at":"2026-08-07T05:17:16.754728Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10362","last_updated":"2024-06-04T08:31:15Z","snapshot_observed_at":"2026-08-03T23:06:17.930023Z","submitted_at":"2023-10-16T12:58:04Z","title":"Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks","version":3},"cited_work":{"arxiv_id":"2310.10362","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10362","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2310.10362 , year=","venue":null,"work_id":"87d344b2-5379-429d-ae6a-ffa325209882","year":2023},"citing_paper":{"arxiv_id":"2507.05311","last_updated":"2026-05-22T09:31:03Z","snapshot_observed_at":"2026-08-03T00:47:40.108614Z","submitted_at":"2025-07-07T09:48:09Z","title":"PLACE: Prompt Learning for Attributed Community Search in Large Graphs","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-25T07:47:47.529586Z"},"links":{"cited_paper":"/paper/2310.10362","citing_paper":"/paper/2507.05311"},"observation_digest":"sha256:cd96aea3d39d3049aebd2e63740c2a4b45f4ddb9faa8763317994e7d1830e222","observation_id":"ff6a806c-83e9-4f66-b8ab-24e85d6799c0","resolution":{"observed_at":"2026-05-25T07:50:29.396067Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10362","last_updated":"2024-06-04T08:31:15Z","snapshot_observed_at":"2026-08-03T23:06:17.930023Z","submitted_at":"2023-10-16T12:58:04Z","title":"Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks","version":3},"cited_work":{"arxiv_id":"2310.10362","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10362","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2310.10362 , year=","venue":null,"work_id":"87d344b2-5379-429d-ae6a-ffa325209882","year":2023},"citing_paper":{"arxiv_id":"2605.12061","last_updated":"2026-05-12T12:47:43Z","snapshot_observed_at":"2026-08-06T07:22:02.201477Z","submitted_at":"2026-05-12T12:47:43Z","title":"SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-05-13T04:45:34.957298Z"},"links":{"cited_paper":"/paper/2310.10362","citing_paper":"/paper/2605.12061"},"observation_digest":"sha256:f01e87b727c1f8e8f74e80dbfcfd726586933a42202d2fafe73fc4ff08397bfb","observation_id":"02837313-f064-4aef-b418-6b419547eca1","resolution":{"observed_at":"2026-05-13T04:52:17.431957Z","resolver_source":"arxiv_id","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/2310.10362/citation-record","integrity":"/paper/2310.10362/integrity","json":"/paper/2310.10362/citation-record.json","paper":"/paper/2310.10362"},"outbound":[],"paper":{"arxiv_id":"2310.10362","last_updated":"2024-06-04T08:31:15Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T23:06:17.930023Z","submitted_at":"2023-10-16T12:58:04Z","title":"Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks"},"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 3 inbound Pith citation observations for arXiv:2310.10362."}