{"as_of":"2026-08-20T08:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c0fc27baed992cfda6bf2bba4c86a3876ca6fe3abbfeb1e1032a8144e1f2978b","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:53:37.214801Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.11803/citation-record","integrity":"/paper/2505.11803/integrity","json":"/paper/2505.11803/citation-record.json","paper":"/paper/2505.11803"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:40.052060Z","title":null,"venue":null,"work_id":"08efff09-a62f-4503-9580-55000bee59b0","year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.278719Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:a46912588f9065a00f7f3f11dce665c42c668cee9cb665e4d00de6bebde270df","observation_id":"0a5529fe-528c-4206-affd-cf4face23e4e","resolution":{"observed_at":"2026-08-15T20:53:40.056752Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.408277Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.408277Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:26c98a2c5dfb3ddb560791c9a58cf7f9cbd6e2f30d757045ec6e0acfbc75f0be","observation_id":"268ab20f-9e56-4de6-9819-71713e0cd067","resolution":{"observed_at":"2026-08-15T20:53:35.408277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.985338Z","title":null,"venue":null,"work_id":"b4f33b72-1677-479d-bdac-f6b2abb3332f","year":2014},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.412431Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:add58aaecc7ac6a931aea9efc9eb9471718a39de88fbddeffa215adcf1b231d4","observation_id":"f0999da7-159c-4c9e-b019-534503a8bb2c","resolution":{"observed_at":"2026-08-15T20:53:39.989495Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.416695Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.416695Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:798387f09c7b84472c46704d34d53ea01df20ec625b5646216b0c7cc09661a68","observation_id":"8ed151ff-78e1-4b8f-871e-1e8eedd80445","resolution":{"observed_at":"2026-08-15T20:53:35.416695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18106","last_updated":"2024-05-28T12:13:07Z","snapshot_observed_at":"2026-08-17T21:13:41.194133Z","submitted_at":"2024-05-28T12:13:07Z","title":"A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation and Extrapolation","version":1},"cited_work":{"arxiv_id":"2405.18106","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.18106","snapshot_observed_at":"2026-08-15T20:53:38.321319Z","title":"A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation and Extrapolation","venue":"cs.AI","work_id":"f8be8518-c281-4a01-a150-34fa3051d955","year":2024},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.424637Z"},"links":{"cited_paper":"/paper/2405.18106","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:de225dc13b377bac08141b2b5785522930954e899322e03b0e1606f6ed1f0990","observation_id":"7be0ad66-109d-420e-af48-196d98fb4401","resolution":{"observed_at":"2026-08-15T20:53:38.326308Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"8380.5194","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.184432Z","title":null,"venue":null,"work_id":"32eed225-8be9-4065-b1b0-f3088fcb15ed","year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.429993Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:9e798cb10a520e30129dc03b74f6a3f9d9f8812b0e1de15ea7f007cd7179ae33","observation_id":"a7875829-4442-4e33-a08e-2729c28f8463","resolution":{"observed_at":"2026-08-15T20:53:38.308438Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.937848Z","title":null,"venue":null,"work_id":"5b648b89-a851-41ee-8c9c-23d0ce5f44ce","year":2014},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.434827Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:802b3552d74457b6f8c2db3bf531f8fdfb1f96de416153d88eee8e26ca3a79ac","observation_id":"53ed2a13-e984-40b4-a990-eb174f20311d","resolution":{"observed_at":"2026-08-15T20:53:39.959560Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.472055Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.472055Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:0ff4b15225d19da4fa59bdda0530d720b47e6b6e12edb35ac007acf392550535","observation_id":"87f40ec3-fab1-43a7-99f5-f4b618b5c23d","resolution":{"observed_at":"2026-08-15T20:53:35.472055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.603675Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.603675Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:7ef7825f153f110c27687aba249d18aa0d2663a33665989673149ea11039daf4","observation_id":"d5ba10b6-760b-4742-b9b9-43d5ab1f875f","resolution":{"observed_at":"2026-08-15T20:53:35.603675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-15T20:53:35.607676Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.607676Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:8eb460f67ea3f4d461b51ac1dd707ea4ce267dcf99702d2448109240e2bae6f3","observation_id":"a73109b1-b650-416e-a3c5-2560c9139bff","resolution":{"observed_at":"2026-08-15T20:53:35.607676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.908557Z","title":null,"venue":null,"work_id":"04444d2d-af16-4fbf-bb35-e41c2f96690e","year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.612266Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:840215f2501374f8013543cd991c67d7464e6e145716677bf9908e97c12c7b55","observation_id":"ec6f3702-dd38-42aa-886d-8be6102f9c3a","resolution":{"observed_at":"2026-08-15T20:53:39.913259Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10219","last_updated":"2024-10-03T21:43:43Z","snapshot_observed_at":"2026-08-16T18:20:09.127438Z","submitted_at":"2023-07-14T21:29:16Z","title":"Temporal Fact Reasoning over Hyper-Relational Knowledge Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10219","snapshot_observed_at":"2026-08-15T20:53:35.617391Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.617391Z"},"links":{"cited_paper":"/paper/2307.10219","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:a7f0b5e8f59c193820dfe03d11f2cccc63707b54260e5603a58c9dfd68a94970","observation_id":"70403604-657c-4d97-a7ed-ac58c662e8a3","resolution":{"observed_at":"2026-08-15T20:53:35.617391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.00137","last_updated":"2020-07-15T13:39:31Z","snapshot_observed_at":"2026-08-18T19:38:59.636984Z","submitted_at":"2019-06-01T03:03:15Z","title":"Knowledge Hypergraphs: Prediction Beyond Binary Relations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.00137","snapshot_observed_at":"2026-08-15T20:53:35.621830Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.621830Z"},"links":{"cited_paper":"/paper/1906.00137","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:ea527e6941e66208f66f16348763cbf89903e4ea1b48da263d0479589d95eece","observation_id":"b3bab488-a0f2-413d-b940-178c62de102a","resolution":{"observed_at":"2026-08-15T20:53:35.621830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.840238Z","title":null,"venue":null,"work_id":"d3687c31-3bd3-415b-8a65-958487d62cc5","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.626425Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:91204dca3f77d6d9832df57c1db1759d825eb8c8ec89a3a9b3a56c3223b34125","observation_id":"f1d98844-b191-404d-8163-73f5f8d579ac","resolution":{"observed_at":"2026-08-15T20:53:39.868980Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.10847","last_updated":"2020-09-22T22:38:54Z","snapshot_observed_at":"2026-08-16T18:16:30.973668Z","submitted_at":"2020-09-22T22:38:54Z","title":"Message Passing for Hyper-Relational Knowledge Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.10847","snapshot_observed_at":"2026-08-15T20:53:35.629944Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.629944Z"},"links":{"cited_paper":"/paper/2009.10847","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:e39051ce508e4574230b8ef3f62721762ac471691c20c0b7628e4aa817bc2419","observation_id":"842804d9-938f-4439-8a9c-d9dbc21a358a","resolution":{"observed_at":"2026-08-15T20:53:35.629944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.634207Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.634207Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:06dc13ba822c032b8b5379353cab0cc185d85e90c65e6cfde7ef9259a75eeadc","observation_id":"8431f25c-78df-484f-b07e-dfbefe8aa5ab","resolution":{"observed_at":"2026-08-15T20:53:35.634207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.808460Z","title":null,"venue":null,"work_id":"5d522293-5770-4a31-86b4-13fd8b13c986","year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.639065Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:d793b18fbbb7184db98e24001fc3fff4415281959147d312b52c1dcd908ea7d6","observation_id":"0cacbfc0-9026-4166-9217-a895007c122e","resolution":{"observed_at":"2026-08-15T20:53:39.822672Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.768212Z","title":null,"venue":null,"work_id":"6348615a-0876-44bd-a262-0382487b4853","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.643388Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:1d0813827347c155fb7af4c12b4e7992ea6ce22a877e52424b8391eab1daea62","observation_id":"5a8db1d2-17ce-4415-b3e1-c06bbca4fed9","resolution":{"observed_at":"2026-08-15T20:53:39.772763Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.748890Z","title":null,"venue":null,"work_id":"9599214f-5d01-474e-a1e9-b2dcea4bdfdb","year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.657270Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:109da53c5188107b40ac926ac8380b7ae027910cb8efedb736c4aee577799dc4","observation_id":"1afcec07-7c39-4a5d-83e5-a31131d2b09c","resolution":{"observed_at":"2026-08-15T20:53:39.759071Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.658783Z","title":null,"venue":null,"work_id":"68b63001-1fbd-42f4-88c7-d68d11221049","year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.822753Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:f773bd5a323555fc67bb641b8a6358caa41897851609451c6246596ec56e7ddd","observation_id":"9d34e89d-65b1-4b02-8089-ce33f488d917","resolution":{"observed_at":"2026-08-15T20:53:39.683411Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:35.920792Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.920792Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:535026094d8c76eb4ba5fcc545ddbd95ec39d76119b13c1a56e1276527e610aa","observation_id":"c94c6b57-b68a-40d5-b0e7-0d0edb4e9b77","resolution":{"observed_at":"2026-08-15T20:53:35.920792Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.692373Z","title":"InProceedings of the 58th annual meeting of the association for computational linguistics","venue":null,"work_id":"825985df-c22e-4ccc-ae49-966ad9867cf0","year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.733262Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:80daf0b96d449d21f0fd782910fb7002877426361b0f4c8c12815cd738547d42","observation_id":"bc2d8c64-86a8-43cd-927f-c90fc69fa813","resolution":{"observed_at":"2026-08-15T20:53:39.697778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.625878Z","title":null,"venue":null,"work_id":"8361baf5-02ad-4b01-a3f7-31193dc6d83d","year":2015},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.960172Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:2c715f13e64cab81581558a919587dd7513828458df6a4b7cd5dcd36638dcfbb","observation_id":"b2b3d1bc-9bcf-434c-9217-e16a5b0f9d45","resolution":{"observed_at":"2026-08-15T20:53:39.631234Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.10595","last_updated":"2020-12-19T04:45:32Z","snapshot_observed_at":"2026-08-17T15:37:38.851436Z","submitted_at":"2020-12-19T04:45:32Z","title":"T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion","version":1},"cited_work":{"arxiv_id":"2012.10595","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.10595","snapshot_observed_at":"2026-08-15T20:53:37.862486Z","title":"T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion","venue":"cs.LG","work_id":"331e2df0-9e1e-4081-8c8a-67b0e0cda811","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.964805Z"},"links":{"cited_paper":"/paper/2012.10595","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:c7b6a827576cf4daeda93c7f570977061565ca55aabc45d875fbf12aca55b189","observation_id":"b8a86fc6-8f7d-4445-ac85-a39d1b6453f9","resolution":{"observed_at":"2026-08-15T20:53:37.952840Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15537","last_updated":"2021-04-01T13:17:47Z","snapshot_observed_at":"2026-08-18T11:48:16.530093Z","submitted_at":"2020-12-31T10:41:01Z","title":"xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.15537","snapshot_observed_at":"2026-08-15T20:53:35.955853Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.955853Z"},"links":{"cited_paper":"/paper/2012.15537","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:9301ec4e5757f1c24ae1aac5aaf8b3f3b71149790533769e5d5815f0c997c383","observation_id":"ac42971b-67f4-486f-ba99-7a62af0afab2","resolution":{"observed_at":"2026-08-15T20:53:35.955853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.569843Z","title":null,"venue":null,"work_id":"b34298ab-ef20-45b4-b85a-831b7b0d84ad","year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.027018Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:ec07cea370db26bba29c646a0437e3c783a222881e2b01d6be6357cfaccf74b0","observation_id":"d74c5dc6-04a3-4a88-8b2f-142e6883dd98","resolution":{"observed_at":"2026-08-15T20:53:39.603600Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.00934","last_updated":"2019-07-18T14:39:54Z","snapshot_observed_at":"2026-08-14T19:49:19.950725Z","submitted_at":"2018-02-03T08:16:31Z","title":"Incorporating Literals into Knowledge Graph Embeddings","version":3},"cited_work":{"arxiv_id":"1802.00934","doi":null,"metadata_source":"pith","pith_arxiv_id":"1802.00934","snapshot_observed_at":"2026-08-15T20:53:37.715311Z","title":"Incorporating Literals into Knowledge Graph Embeddings","venue":"cs.AI","work_id":"7fc3f1b0-fbc2-4b7d-8e59-aaedb241e8f3","year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.102429Z"},"links":{"cited_paper":"/paper/1802.00934","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:8df5b9ff013e90f667e08b0d2720d5ecccfed4535b82e06edc4f5bc39c4aaaa4","observation_id":"040d03d5-8083-461e-968f-5e9d19f67e91","resolution":{"observed_at":"2026-08-15T20:53:37.780597Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-08-17T10:49:36.026134Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-15T20:53:35.970076Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.970076Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:f4d59413490a6cea7fdedbadfd0d6977e0881a3dd2266db67940162db49a986f","observation_id":"2299035c-28b0-44a5-a879-654a7085c9ab","resolution":{"observed_at":"2026-08-15T20:53:35.970076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.556156Z","title":null,"venue":null,"work_id":"77f6b67d-3362-41d7-af47-bd981ed29d4e","year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.188452Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:3235f50e26234afe6e51690494d54f428b75a21ba0c35e936dfe84a0d8727962","observation_id":"f558ac92-ee84-4eda-9a45-aba15db78381","resolution":{"observed_at":"2026-08-15T20:53:39.561415Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.488585Z","title":null,"venue":null,"work_id":"1ad2598f-1622-4dfa-a2f3-b80fee3c3251","year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.193034Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:934423c541f6899631de7d82956f6732e80a4131afcae56bb0b93d2987bb0fb3","observation_id":"3a9e8222-ef0c-45d4-86b9-9a29f40a1035","resolution":{"observed_at":"2026-08-15T20:53:39.535654Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.04926","last_updated":"2020-04-10T07:09:30Z","snapshot_observed_at":"2026-08-05T19:44:25.297690Z","submitted_at":"2020-04-10T07:09:30Z","title":"Tensor Decompositions for temporal knowledge base completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.04926","snapshot_observed_at":"2026-08-15T20:53:36.182797Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.182797Z"},"links":{"cited_paper":"/paper/2004.04926","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:d86e2a804d4f5cddd09f9b0a8c6a46be572938de6b1d380bfa3076a48c5973d8","observation_id":"62321268-fc9e-4031-bcd6-ebe8083a318a","resolution":{"observed_at":"2026-08-15T20:53:36.182797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.00327","last_updated":"2021-06-01T09:01:22Z","snapshot_observed_at":"2026-08-16T18:20:37.994350Z","submitted_at":"2021-06-01T09:01:22Z","title":"Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.00327","snapshot_observed_at":"2026-08-15T20:53:36.202615Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.202615Z"},"links":{"cited_paper":"/paper/2106.00327","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:e2174cadf4ed2ccf3dc4de47867265c10c62be04e5f713e7d972a80182688631","observation_id":"460d23d0-1145-4aa6-bc2f-7cea1911fac0","resolution":{"observed_at":"2026-08-15T20:53:36.202615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.354830Z","title":null,"venue":null,"work_id":"fb74e225-2432-42ed-8bbc-10f1b14c05cb","year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.304291Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:e49fc61b38d720afa3d532d0133390d13fe7e935073e199bf342e8ec7cb12d07","observation_id":"758bd9d6-e893-4d40-9712-9d3c006a5384","resolution":{"observed_at":"2026-08-15T20:53:39.400602Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.462240Z","title":null,"venue":null,"work_id":"be73e5ce-3fd5-400e-8592-6afa7c93326a","year":2022},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.197652Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:5f6ddc3469ab3c50d1875b1f74dbca63c1ef067efb5c1e41308016857d1ecf76","observation_id":"ff782384-292f-483a-8e8a-226888958c4c","resolution":{"observed_at":"2026-08-15T20:53:39.466706Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.332883Z","title":null,"venue":null,"work_id":"5b8214f7-bd1d-45aa-8dbf-869a0572a440","year":2022},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.524021Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:7df4480da61ec1d109ceea987b3ce8f422c13595168ac70629230e0a8dc90345","observation_id":"5088075c-9df4-4f51-be9d-3edb5e2709b6","resolution":{"observed_at":"2026-08-15T20:53:39.337281Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.227581Z","title":null,"venue":null,"work_id":"da280c9a-9ea3-4aec-ab8e-0425271f24ee","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.528256Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:03d6408413c26f6e48ff2c73ce20c040e9eb027ba1c5ccf38ec9ef7b03a1abf5","observation_id":"bb457167-82ae-4f74-9983-b8647a725e43","resolution":{"observed_at":"2026-08-15T20:53:39.232230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.436431Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.436431Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:017133811f40b9894f06f608a1d6e30568a615c8c37bf985a0acd6f7680b8130","observation_id":"d5ecee1c-4da8-47e5-8297-d6f96f6d38d2","resolution":{"observed_at":"2026-08-15T20:53:36.436431Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.132950Z","title":null,"venue":null,"work_id":"4efe2124-d473-4216-a259-bf352d51e7fb","year":2022},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.536929Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:85c87d77b01fa2cf61bf856124f69be587a2ffe8a2231ea8f254a65508bfd2a0","observation_id":"0b6d8671-fff9-4e80-a0ec-cc708e7b3f0a","resolution":{"observed_at":"2026-08-15T20:53:39.206260Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.02121","last_updated":"2018-03-13T07:45:20Z","snapshot_observed_at":"2026-08-14T20:06:21.462280Z","submitted_at":"2017-12-06T10:41:47Z","title":"A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.02121","snapshot_observed_at":"2026-08-15T20:53:36.540458Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.540458Z"},"links":{"cited_paper":"/paper/1712.02121","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:4c3ee5eca3ea6a97e8b017e139866d0028db7fe1aff7a9904ff2c860461c605b","observation_id":"2952278c-d9bd-416c-a2f5-1b17f49458f9","resolution":{"observed_at":"2026-08-15T20:53:36.540458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.215809Z","title":null,"venue":null,"work_id":"be4ae8e7-681e-4229-b99b-e8d25f0ef910","year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.532808Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:dfc635451fe43b3f8f93f1b02057fcd2df0f3e351c66fad5ce8993bea53c7df5","observation_id":"ee675ad9-d2a5-476f-baa3-d57de73fe5e9","resolution":{"observed_at":"2026-08-15T20:53:39.220285Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.030661Z","title":null,"venue":null,"work_id":"cbb11ede-9a5a-4a09-97da-1e9394eb2293","year":2024},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.548673Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:cae6adc8f8053c9c98ad92ff39765fe28030847ad668a82c08c7d4c138a75079","observation_id":"01473de3-48aa-4a73-abb8-fc32cf53fa18","resolution":{"observed_at":"2026-08-15T20:53:39.061929Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.856956Z","title":null,"venue":null,"work_id":"1a23e7f7-b49b-485a-a849-c4c3ca21904a","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.648365Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:e9b71e08278daa231e0c0567b6a77b9a81df91da371091833ddb5115526807f0","observation_id":"6dd66eb4-79f9-446f-8210-9535c7f9a238","resolution":{"observed_at":"2026-08-15T20:53:38.918887Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:39.072451Z","title":null,"venue":null,"work_id":"3cf22734-534b-4aa8-a768-6bd68c2c4e9f","year":2011},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.545325Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:5e9eafc18760d123ed846ba0ea9d9c4c53450d7552e76b2450d030233ab4253e","observation_id":"a1df7ade-5421-4a6f-b77c-d06b01e6a352","resolution":{"observed_at":"2026-08-15T20:53:39.078063Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.691083Z","title":null,"venue":null,"work_id":"1d0135e6-4b46-4f44-ab2c-ff64d39371a2","year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.784266Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:4b247b7c9501941106632478266ff2c4f4fdd4694c3c09e1c6688fe287baeb9b","observation_id":"02693923-2627-467f-9d6f-5241178586bd","resolution":{"observed_at":"2026-08-15T20:53:38.801471Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.613703Z","title":null,"venue":null,"work_id":"f8cc0f5d-4e5f-4a69-aafa-7b9ee9a7fc87","year":2024},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.788716Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:2476cf0ead33c50ae5dd56b85cffbff4f8f7d677e217b86d640fa9571adcdcfe","observation_id":"a42c66db-02cf-42dd-bb32-603609f60dcb","resolution":{"observed_at":"2026-08-15T20:53:38.617876Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.843501Z","title":null,"venue":null,"work_id":"999eb94d-63e5-4721-b7c3-81bed2abd873","year":2022},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.737747Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:cadb81ba677ca6d5eb4ed3e478c8a1dc57ca618af4cfe4f6a0f24bde3b6b15d7","observation_id":"64dd82d1-c745-4f13-bf4f-59078adf0126","resolution":{"observed_at":"2026-08-15T20:53:38.847961Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.799977Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.799977Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:8786855ed1c816376130c47af5aa49efb3f0a7a945d09e0c1aed51c9e9a0a85e","observation_id":"4d5ab311-1545-4037-8700-3619e535b32e","resolution":{"observed_at":"2026-08-15T20:53:36.799977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.582676Z","title":null,"venue":null,"work_id":"33c27d58-41d3-4e13-9630-71b7c729ec64","year":2023},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.804344Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:75e6b01d8964811fde6649367616eb5b4292c1f8821bf19e9095b744083149ff","observation_id":"73cb265c-f5c9-4b6f-b895-5687a8440ab2","resolution":{"observed_at":"2026-08-15T20:53:38.586882Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.794499Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.794499Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:c2ba0a546bdbd475054dc9c79c529463f271e4b73450dd7328f5688643448bed","observation_id":"c9d53d6c-3c83-43de-a18d-6f3efbae34fd","resolution":{"observed_at":"2026-08-15T20:53:36.794499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08476","last_updated":"2021-05-18T12:40:35Z","snapshot_observed_at":"2026-08-16T18:23:57.908101Z","submitted_at":"2021-05-18T12:40:35Z","title":"Link Prediction on N-ary Relational Facts: A Graph-based Approach","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08476","snapshot_observed_at":"2026-08-15T20:53:36.815552Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.815552Z"},"links":{"cited_paper":"/paper/2105.08476","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:555dcae4d0bedca50f50745d188a2f4822b066032e896ad39d3926afed56b3d9","observation_id":"036b8bd9-69dd-45bb-8f0e-1a2f490fa0a0","resolution":{"observed_at":"2026-08-15T20:53:36.815552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.819951Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.819951Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:29a932bb2e9d47c4fbd3d311401bf70041cbc6335e30511c26e971e3bae34983","observation_id":"2e3be3e0-563d-41fa-8c84-52ba63ecc073","resolution":{"observed_at":"2026-08-15T20:53:36.819951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.810581Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.810581Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:396f039cc227854274a92f10ddf53271faf3a24392fe270399253d31446f3bc3","observation_id":"b88767c2-aa57-49ee-9da7-cc5595e0e474","resolution":{"observed_at":"2026-08-15T20:53:36.810581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1604.08642","last_updated":"2016-04-28T22:42:38Z","snapshot_observed_at":"2026-08-14T21:59:36.694163Z","submitted_at":"2016-04-28T22:42:38Z","title":"On the representation and embedding of knowledge bases beyond binary relations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1604.08642","snapshot_observed_at":"2026-08-15T20:53:36.979789Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.979789Z"},"links":{"cited_paper":"/paper/1604.08642","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:0d8c3b5f91020de19f7210d602cc5248161df4a364c1718939ea08ea6c376b38","observation_id":"8a08878c-785c-417c-93fb-a67f63ed46cc","resolution":{"observed_at":"2026-08-15T20:53:36.979789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.03526","last_updated":"2020-10-07T17:11:53Z","snapshot_observed_at":"2026-08-17T04:18:28.517924Z","submitted_at":"2020-10-07T17:11:53Z","title":"TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.03526","snapshot_observed_at":"2026-08-15T20:53:36.983882Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.983882Z"},"links":{"cited_paper":"/paper/2010.03526","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:a7032f58c8c8acfe4b691e5a8144c5223aa00c2c88ceba2d6bc3c93a11a8b454","observation_id":"cbdb6821-ad61-42ce-b304-5c3cab2a0201","resolution":{"observed_at":"2026-08-15T20:53:36.983882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.879661Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.879661Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:f3fffbfdc622daa2562b0f37ca459da007bdf59575f19952d54f57d91d45a55a","observation_id":"1eb8e8e3-7af0-40e9-b728-ea9be8b44067","resolution":{"observed_at":"2026-08-15T20:53:36.879661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.01029","last_updated":"2020-10-24T22:42:26Z","snapshot_observed_at":"2026-08-16T20:08:17.237690Z","submitted_at":"2020-10-02T14:35:27Z","title":"TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation","version":2},"cited_work":{"arxiv_id":"2010.01029","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.01029","snapshot_observed_at":"2026-08-15T20:53:37.494546Z","title":"TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation","venue":"cs.CL","work_id":"5051049d-42f6-4da5-b08b-d0b7ae8c15a3","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.993361Z"},"links":{"cited_paper":"/paper/2010.01029","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:0ebb2f47edc9e2407af8d67a212787ba28442ed5d564625ca13d6532b4614ff3","observation_id":"e4bdfd47-468c-4230-be20-0216aa7f799f","resolution":{"observed_at":"2026-08-15T20:53:37.616817Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:36.998360Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.998360Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:a59b8b551f3cf33c80f5b0ff01b41e8d0cc14888d294911e62289cc78521b4a0","observation_id":"5ffa8d9b-3a38-43de-bf91-f300ebbef7c9","resolution":{"observed_at":"2026-08-15T20:53:36.998360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.07893","last_updated":"2020-10-28T12:28:46Z","snapshot_observed_at":"2026-07-06T08:37:56.926157Z","submitted_at":"2019-11-18T19:36:26Z","title":"Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.07893","snapshot_observed_at":"2026-08-15T20:53:36.988846Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:36.988846Z"},"links":{"cited_paper":"/paper/1911.07893","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:a02b932882430754e3d21cc5a928bd4cf8fb78f9efd0a4f2cfdd0ddae0fb4c98","observation_id":"7a423df1-3302-472b-9373-9abe9239c426","resolution":{"observed_at":"2026-08-15T20:53:36.988846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08167","last_updated":"2021-04-16T15:26:41Z","snapshot_observed_at":"2026-08-18T12:27:42.309537Z","submitted_at":"2021-04-16T15:26:41Z","title":"Improving Hyper-Relational Knowledge Graph Completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08167","snapshot_observed_at":"2026-08-15T20:53:37.062783Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.062783Z"},"links":{"cited_paper":"/paper/2104.08167","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:c983d0fa18a16591fa8176daeb6e95d92c5576f59f7e7c8e9da3bc4704ae9add","observation_id":"70035cb3-713d-4261-8322-92c7d556b37b","resolution":{"observed_at":"2026-08-15T20:53:37.062783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.541001Z","title":null,"venue":null,"work_id":"35c4e5e6-8daa-4f01-a350-2e8b6a778f8b","year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.136148Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:04613ab81e956a66e6dcbe34a66fc8f9c26d7d381a8f8955fff39bbef3631d1e","observation_id":"f9f875cc-dc7f-4a0d-9b04-a0f64f581c80","resolution":{"observed_at":"2026-08-15T20:53:38.544793Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.07962","last_updated":"2020-02-19T02:05:37Z","snapshot_observed_at":"2026-08-18T19:24:58.405240Z","submitted_at":"2020-02-19T02:05:37Z","title":"Inductive Representation Learning on Temporal Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.07962","snapshot_observed_at":"2026-08-15T20:53:37.002944Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.002944Z"},"links":{"cited_paper":"/paper/2002.07962","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:3acf401825d55cc8c950de9cd8153df69cdbc2f92932cd19f46d4b7fb74637c2","observation_id":"14057411-3215-428a-8a88-45a76cb919fd","resolution":{"observed_at":"2026-08-15T20:53:37.002944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6575","last_updated":"2015-08-29T15:08:45Z","snapshot_observed_at":"2026-08-14T23:06:41.229837Z","submitted_at":"2014-12-20T01:37:16Z","title":"Embedding Entities and Relations for Learning and Inference in Knowledge Bases","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6575","snapshot_observed_at":"2026-08-15T20:53:37.008534Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.008534Z"},"links":{"cited_paper":"/paper/1412.6575","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:3ff37ffd9354cb48271c2664e554be182141589cecda13f1751b78985981ae86","observation_id":"f7c39651-4c33-497b-a699-6b6f34bccb90","resolution":{"observed_at":"2026-08-15T20:53:37.008534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:37.150773Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.150773Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:fcf3a1d30fa171526d52c41c0b9f7120eb43ee7ac6a2755766223951bc78b60a","observation_id":"56b61649-1e47-4183-b9cf-2e33b1f43dbd","resolution":{"observed_at":"2026-08-15T20:53:37.150773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.08401","last_updated":"2022-04-29T02:38:44Z","snapshot_observed_at":"2026-08-19T16:01:00.366325Z","submitted_at":"2022-04-18T16:55:25Z","title":"TranS: Transition-based Knowledge Graph Embedding with Synthetic Relation Representation","version":2},"cited_work":{"arxiv_id":"2204.08401","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.08401","snapshot_observed_at":"2026-08-15T20:53:37.397438Z","title":"TranS: Transition-based Knowledge Graph Embedding with Synthetic Relation Representation","venue":"cs.CL","work_id":"cce0c5f7-270f-4c62-b801-ecf3d8dea3ed","year":2022},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.141228Z"},"links":{"cited_paper":"/paper/2204.08401","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:8c7518c8f1432aa05f04c8edcec91123dbbd1f70fa56b4c4cbc0b76055846b60","observation_id":"40746daa-2081-4473-929f-58f938b2ed5b","resolution":{"observed_at":"2026-08-15T20:53:37.444024Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.529358Z","title":null,"venue":null,"work_id":"335f9f9a-4f94-4b3b-86c2-a86ddc34179b","year":2024},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.145697Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:8580a9329f997c44f75aa04a02fb9f4eb7aea60b73f6037b5fc0d10b9c1b317e","observation_id":"0f9bef64-632b-4153-9344-28b0e370f283","resolution":{"observed_at":"2026-08-15T20:53:38.533581Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:40.006047Z","title":null,"venue":null,"work_id":"7140351f-1837-4517-bfe5-260c5167ce19","year":2020},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.337052Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:6b9795597d2321f9e3925fae3e1f16ca2d873db70f6b03eee623b8ecb3205598","observation_id":"9c57c841-5d4d-4f80-83da-bcb99bd03084","resolution":{"observed_at":"2026-08-15T20:53:40.042653Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:53:38.347224Z","title":"InProceedings of the AAAI conference on artificial intelligence, Vol","venue":null,"work_id":"98f2841a-d7f8-4756-876a-79157e051839","year":2018},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:37.214801Z"},"links":{"citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:9d457e41be9944cfad0e6cf96a48b1d7683f70e04fa8c42bba74e1b97ff1de08","observation_id":"13aa6f95-8002-45f7-b278-b136f5028d58","resolution":{"observed_at":"2026-08-15T20:53:38.412476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04782","last_updated":"2024-03-02T16:21:45Z","snapshot_observed_at":"2026-08-16T14:13:28.434110Z","submitted_at":"2024-03-02T16:21:45Z","title":"A Survey on Temporal Knowledge Graph: Representation Learning and Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04782","snapshot_observed_at":"2026-08-15T20:53:35.420210Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-15T20:53:35.420210Z"},"links":{"cited_paper":"/paper/2403.04782","citing_paper":"/paper/2505.11803"},"observation_digest":"sha256:769a67e06c5a77fea6141f6027b19fbeb6da537257ffb18c5b819559c154247e","observation_id":"fb65c916-a3c7-414a-beac-e9290d4a3ae6","resolution":{"observed_at":"2026-08-15T20:53:35.420210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.11803","last_updated":"2025-05-17T03:16:13Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-16T18:16:55.041126Z","submitted_at":"2025-05-17T03:16:13Z","title":"VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":60,"verified_exact":6,"verified_fuzzy":2},"total_outbound_references":68},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2505.11803."}