{"as_of":"2026-08-11T20:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e5ae12c19774ba16716d54cc44f0c4b27042a8845de4b1805a476793b4bd01e4","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":"2026-08-11T06:34:44.6726+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":"2026-08-10T16:50:52.712362Z","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":"2026-06-29T08:43:15.509485Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.12268","last_updated":"2023-05-20T19:17:10Z","snapshot_observed_at":"2026-08-03T02:33:34.894752Z","submitted_at":"2023-05-20T19:17:10Z","title":"Patton: Language Model Pretraining on Text-Rich Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.12268","snapshot_observed_at":"2026-08-10T16:50:52.712362Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12857","last_updated":"2025-01-22T13:09:09Z","snapshot_observed_at":"2026-08-10T16:40:16.521722Z","submitted_at":"2025-01-22T13:09:09Z","title":"HierPromptLM: A Pure PLM-based Framework for Representation Learning on Heterogeneous Text-rich Networks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T16:50:52.712362Z"},"links":{"cited_paper":"/paper/2305.12268","citing_paper":"/paper/2501.12857"},"observation_digest":"sha256:b6d35a0406425c1a2d9691bb29df0b7d8a0e2b7c1bece8c2baf97e762aae7471","observation_id":"1c98db87-d1e8-4482-aa23-517736de4bab","resolution":{"observed_at":"2026-08-10T16:50:52.712362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.12268","last_updated":"2023-05-20T19:17:10Z","snapshot_observed_at":"2026-08-03T02:33:34.894752Z","submitted_at":"2023-05-20T19:17:10Z","title":"Patton: Language Model Pretraining on Text-Rich Networks","version":1},"cited_work":{"arxiv_id":"2305.12268","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.12268","snapshot_observed_at":"2026-06-29T08:43:15.509485Z","title":null,"venue":null,"work_id":"29e14a50-7663-4260-85e2-54e0408e6833","year":2023},"citing_paper":{"arxiv_id":"2603.01410","last_updated":"2026-04-15T12:49:26Z","snapshot_observed_at":"2026-08-11T13:51:16.081832Z","submitted_at":"2026-03-02T03:25:40Z","title":"GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-15T18:47:06.207176Z"},"links":{"cited_paper":"/paper/2305.12268","citing_paper":"/paper/2603.01410"},"observation_digest":"sha256:c9b0430bae6f53591d1ffafae5a444dfb4229a7114d4eb7d8fdd0fc56f302b30","observation_id":"da47f4f7-f529-47d7-b790-00ed08b53d07","resolution":{"observed_at":"2026-05-15T18:50:16.964241Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.12268","last_updated":"2023-05-20T19:17:10Z","snapshot_observed_at":"2026-08-03T02:33:34.894752Z","submitted_at":"2023-05-20T19:17:10Z","title":"Patton: Language Model Pretraining on Text-Rich Networks","version":1},"cited_work":{"arxiv_id":"2305.12268","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.12268","snapshot_observed_at":"2026-06-29T08:43:15.509485Z","title":null,"venue":null,"work_id":"29e14a50-7663-4260-85e2-54e0408e6833","year":2023},"citing_paper":{"arxiv_id":"2605.30247","last_updated":"2026-05-28T17:12:48Z","snapshot_observed_at":"2026-08-03T14:56:07.937941Z","submitted_at":"2026-05-28T17:12:48Z","title":"OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-29T08:36:52.151369Z"},"links":{"cited_paper":"/paper/2305.12268","citing_paper":"/paper/2605.30247"},"observation_digest":"sha256:f6e1b65ad42501b3143ce1ef5e5ffaf4b16f6321c201e306e74318b54b31d417","observation_id":"586e6f3d-d3f1-4bdf-8f24-f7c63edc072b","resolution":{"observed_at":"2026-06-29T08:43:15.510908Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.12268/citation-record","integrity":"/paper/2305.12268/integrity","json":"/paper/2305.12268/citation-record.json","paper":"/paper/2305.12268"},"outbound":[],"paper":{"arxiv_id":"2305.12268","last_updated":"2023-05-20T19:17:10Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-03T02:33:34.894752Z","submitted_at":"2023-05-20T19:17:10Z","title":"Patton: Language Model Pretraining on Text-Rich 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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.12268."}