{"as_of":"2026-08-08T13:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:629c933ea8111eb3fc4f2fe8faed2206c802c1502459b96436363223724d0e69","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":"2026-08-07T15:42:25.931255Z","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":"2026-05-11T12:51:06.773645Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.04101","last_updated":"2021-09-09T08:41:01Z","snapshot_observed_at":"2026-08-03T11:36:15.726452Z","submitted_at":"2021-09-09T08:41:01Z","title":"TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04101","snapshot_observed_at":"2026-08-07T15:42:25.931255Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.14020","last_updated":"2025-05-29T07:45:13Z","snapshot_observed_at":"2026-08-08T01:32:27.239864Z","submitted_at":"2025-05-20T07:22:03Z","title":"Disentangled Multi-span Evolutionary Network against Temporal Knowledge Graph Reasoning","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:25.931255Z"},"links":{"cited_paper":"/paper/2109.04101","citing_paper":"/paper/2505.14020"},"observation_digest":"sha256:3620df1b2144670d5ee1d77a7fe0209e01212b89a48588aae869e7bc74c2a072","observation_id":"84b6f107-b92a-407b-b462-f74da8ff1786","resolution":{"observed_at":"2026-08-07T15:42:25.931255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04101","last_updated":"2021-09-09T08:41:01Z","snapshot_observed_at":"2026-08-03T11:36:15.726452Z","submitted_at":"2021-09-09T08:41:01Z","title":"TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04101","snapshot_observed_at":"2026-08-07T14:46:00.140730Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.17794","last_updated":"2025-05-23T12:11:40Z","snapshot_observed_at":"2026-08-07T14:38:25.333334Z","submitted_at":"2025-05-23T12:11:40Z","title":"RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T14:46:00.140730Z"},"links":{"cited_paper":"/paper/2109.04101","citing_paper":"/paper/2505.17794"},"observation_digest":"sha256:477742d270730e522467bbdd599502c08a139bbcb31bb0c99d559cfe9aa51eaf","observation_id":"fa828a26-33df-4692-8ecb-1ca27834e39d","resolution":{"observed_at":"2026-08-07T14:46:00.140730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04101","last_updated":"2021-09-09T08:41:01Z","snapshot_observed_at":"2026-08-03T11:36:15.726452Z","submitted_at":"2021-09-09T08:41:01Z","title":"TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting","version":1},"cited_work":{"arxiv_id":"2109.04101","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.04101","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2109.04101 , year=","venue":null,"work_id":"7d11898e-7022-4cc3-baa7-918652f26e60","year":null},"citing_paper":{"arxiv_id":"2604.19042","last_updated":"2026-04-21T03:48:50Z","snapshot_observed_at":"2026-07-06T23:05:44.499005Z","submitted_at":"2026-04-21T03:48:50Z","title":"STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-10T02:40:21.647700Z"},"links":{"cited_paper":"/paper/2109.04101","citing_paper":"/paper/2604.19042"},"observation_digest":"sha256:9d27ba68bd5184f5df430238b8befed35c635950035ab81a529f29d9419969aa","observation_id":"74c105c0-475a-4832-b373-a4f215752601","resolution":{"observed_at":"2026-05-11T12:51:06.779029Z","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/2109.04101/citation-record","integrity":"/paper/2109.04101/integrity","json":"/paper/2109.04101/citation-record.json","paper":"/paper/2109.04101"},"outbound":[],"paper":{"arxiv_id":"2109.04101","last_updated":"2021-09-09T08:41:01Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T11:36:15.726452Z","submitted_at":"2021-09-09T08:41:01Z","title":"TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting"},"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:2109.04101."}