{"as_of":"2026-08-09T20:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a4db68be1177a31b0c0e6c2fc8dd2793463316316310a46ff2531ae4f5d73d05","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:55:30.563418Z","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":"2026-05-10T05:56:11.424693Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1906.07510","last_updated":"2020-09-06T15:17:00Z","snapshot_observed_at":"2026-07-06T08:01:06.889849Z","submitted_at":"2019-06-18T11:55:16Z","title":"Attention Guided Graph Convolutional Networks for Relation Extraction","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.07510","snapshot_observed_at":"2026-08-07T00:55:30.563418Z","title":"Attention guided graph convolutional networks for relation extraction,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2506.12452","last_updated":"2025-06-14T11:12:34Z","snapshot_observed_at":"2026-08-08T23:36:45.415783Z","submitted_at":"2025-06-14T11:12:34Z","title":"A Pluggable Multi-Task Learning Framework for Sentiment-Aware Financial Relation Extraction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T00:55:30.563418Z"},"links":{"cited_paper":"/paper/1906.07510","citing_paper":"/paper/2506.12452"},"observation_digest":"sha256:5c223e8eb37c0193a2201d315d19e3922d847d5fa23c21436f13f1069f057f78","observation_id":"efcff6d3-7aaa-4313-802c-8ffbf7074bd7","resolution":{"observed_at":"2026-08-07T00:55:30.563418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.07510","last_updated":"2020-09-06T15:17:00Z","snapshot_observed_at":"2026-07-06T08:01:06.889849Z","submitted_at":"2019-06-18T11:55:16Z","title":"Attention Guided Graph Convolutional Networks for Relation Extraction","version":8},"cited_work":{"arxiv_id":"1906.07510","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.07510","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:1906.07510 , year=","venue":null,"work_id":"f6e855f8-629a-42b0-a29a-4ea7eeb53d27","year":1906},"citing_paper":{"arxiv_id":"2604.17458","last_updated":"2026-04-21T06:43:15Z","snapshot_observed_at":"2026-07-06T23:04:32.734175Z","submitted_at":"2026-04-19T14:18:49Z","title":"EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval","version":2},"reference_index":277,"source":"arxiv_source","source_observed_at":"2026-05-10T05:43:04.813867Z"},"links":{"cited_paper":"/paper/1906.07510","citing_paper":"/paper/2604.17458"},"observation_digest":"sha256:809819c2d3552b7ba49f0cc33ee14c0b30e0b85da80468795d1c21ed94e938a0","observation_id":"97e67648-fe60-42d4-a6eb-ae3f3411c490","resolution":{"observed_at":"2026-05-10T05:56:11.425935Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/1906.07510/citation-record","integrity":"/paper/1906.07510/integrity","json":"/paper/1906.07510/citation-record.json","paper":"/paper/1906.07510"},"outbound":[],"paper":{"arxiv_id":"1906.07510","last_updated":"2020-09-06T15:17:00Z","latest_version":8,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T08:01:06.889849Z","submitted_at":"2019-06-18T11:55:16Z","title":"Attention Guided Graph Convolutional Networks for Relation Extraction"},"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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1906.07510."}