{"as_of":"2026-08-08T01:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5ebf538f56f9a7dd03c76a5b994116e6f1f353da7d4a5166c1948c04d528bdc2","coverage":[{"denominator":84,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":84,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:09:34.377982Z","state":"measured"},{"denominator":85,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":85,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T06:26:39.005777Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-04T12:16:13.904932Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"cited_work":{"arxiv_id":"2507.14475","doi":"10.48550/arxiv.2507.14475","metadata_source":"pith","pith_arxiv_id":"2507.14475","snapshot_observed_at":"2026-08-04T12:16:13.904932Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","venue":"cs.DB","work_id":"ef685b5f-9783-4582-8608-a653e615854e","year":2025},"citing_paper":{"arxiv_id":"2601.10485","last_updated":"2026-08-02T18:15:20Z","snapshot_observed_at":"2026-08-07T03:05:10.281208Z","submitted_at":"2026-01-15T15:06:56Z","title":"Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge","version":4},"reference_index":116,"source":"pdf_text","source_observed_at":"2026-08-04T06:26:39.005777Z"},"links":{"cited_paper":"/paper/2507.14475","citing_paper":"/paper/2601.10485"},"observation_digest":"sha256:335cdba465e86270e88537071a05faabf84cdaf406ea2085fa1257cb13ac514f","observation_id":"7783a03e-fcdc-4a10-ba56-e4ec9ac294ae","resolution":{"observed_at":"2026-08-04T06:28:22.515945Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.14475/citation-record","integrity":"/paper/2507.14475/integrity","json":"/paper/2507.14475/citation-record.json","paper":"/paper/2507.14475"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.16457","last_updated":"2024-06-05T05:23:21Z","snapshot_observed_at":"2026-07-06T17:35:23.161066Z","submitted_at":"2024-02-26T09:59:04Z","title":"RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering","version":2},"cited_work":{"arxiv_id":"2402.16457","doi":"10.48550/arxiv.2402.16457","metadata_source":"pith","pith_arxiv_id":"2402.16457","snapshot_observed_at":"2026-08-06T18:16:30.548575Z","title":"RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering","venue":"cs.CL","work_id":"ee29d712-8aa0-498f-acf9-a7f9e6bd1880","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:26.391856Z"},"links":{"cited_paper":"/paper/2402.16457","citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:97a883d8aa8d157e53dad49de8fc005467492d9f09e16f79dacc21d10018a0a1","observation_id":"e5650e82-41b1-4b09-9c50-3b5029c2af90","resolution":{"observed_at":"2026-08-06T16:09:35.103901Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.34350","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:36.517521Z","title":"Inductive meta-path learning for schema-complex heterogeneous information networks,","venue":null,"work_id":"ae2155b6-9c73-4c7a-8e84-e4fc5a65e47b","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:26.494189Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:de8d0a191dcc581fc821100199941b0756f4d0a2464d64245aab68d3d0840fd3","observation_id":"2a18c299-e531-43f9-ae05-a974fcf0ed00","resolution":{"observed_at":"2026-08-06T16:09:36.521635Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:26.608786Z","title":"INFER: A neural-symbolic model for extrapolation reasoning on temporal knowledge graph,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:26.608786Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:c80de7080bd24ab5c2a0aa93e08697b61a287653b34ed256e17658c3bf83c0fa","observation_id":"e2d65225-6584-4b65-ab5b-bb94a305d1b1","resolution":{"observed_at":"2026-08-06T16:09:26.608786Z","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":"2026-08-06T16:09:26.822447Z","title":"Time-aware entity alignment using temporal relational attention,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:26.822447Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:d14f18a429338a38c0e450a64421b2faddc99492ad9deefb864cecbffc9b2928","observation_id":"0ef8140e-fa81-4ae3-89f7-116264fd05e3","resolution":{"observed_at":"2026-08-06T16:09:26.822447Z","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":"2026-08-06T16:09:26.921090Z","title":"Time-aware graph neural network for entity alignment between temporal knowledge graphs,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:26.921090Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:dc0907d09fa5946a3ce963a2f8191431aa8c962aed6d7bcb5884217f4ffeef07","observation_id":"ce65217a-b21e-4aea-8cdf-c029fa7fad75","resolution":{"observed_at":"2026-08-06T16:09:26.921090Z","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":"2026-08-06T16:09:27.020263Z","title":"An effective and efficient time-aware entity alignment framework via two-aspect three-view label propagation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.020263Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:29f14f2022885a48922758f98952f2b38392bc4e9f1cfdedee11068b66c11d0b","observation_id":"62cab600-64a6-4d9a-8b5f-f767f64290b4","resolution":{"observed_at":"2026-08-06T16:09:27.020263Z","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":"2026-08-06T16:09:27.126598Z","title":"Unsupervised entity alignment for temporal knowledge graphs,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.126598Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:ef37e7ca4233f9755b6648beaa6b8a15b4ede6364b66d2b8bfa707768a6389a0","observation_id":"439d6a4a-4677-47ca-b281-7f558eb5f36e","resolution":{"observed_at":"2026-08-06T16:09:27.126598Z","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":"9334.36457","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:36.191999Z","title":"Toward practical entity alignment method design: Insights from new highly heterogeneous knowledge graph datasets,","venue":null,"work_id":"9661e2e2-4755-4097-8890-602aa758336c","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.201332Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:3a799956e0e866279a6e1cd8c4a25d28666e7221b4ee88f0eb7dd7fc90128c09","observation_id":"e27e7737-5aa2-4c99-afd4-fd168d7a6ad5","resolution":{"observed_at":"2026-08-06T16:09:36.196711Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.899112Z","title":"Temporal knowledge graph entity alignment via representation learning,","venue":null,"work_id":"e51bccb0-1065-424c-8ab3-d86d9c0949c3","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.274830Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:774e307202425ae521db13d7981a2ecbbac1841446dd40194a2b7cdcf8ecf071","observation_id":"42d84b91-266a-4950-94f8-1b3200a7116e","resolution":{"observed_at":"2026-08-06T16:09:36.901702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.891251Z","title":"Enhancing knowledge graph attention by temporal modeling for entity alignment with sparse seeds,","venue":null,"work_id":"d1aa2c0c-c403-4fa4-b37e-038f8a61d3d8","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.348259Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:3ecf0992795609f52b9d55070a1f535736fae66662eaf9054d1c396aaf3fb620","observation_id":"b9db0d57-27b6-41b2-8ad3-901c778ea078","resolution":{"observed_at":"2026-08-06T16:09:36.894099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.883469Z","title":"A simple temporal information matching mechanism for entity alignment between temporal knowledge graphs,","venue":null,"work_id":"a48869aa-4cbf-4d88-96aa-e1f26536ee70","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.416918Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:7047171d90ffc2761bbfbd8107b6f5385b7bfd60194e9d5526cae2c068a50111","observation_id":"8107d987-81fa-4170-8c13-5ac547bdf66c","resolution":{"observed_at":"2026-08-06T16:09:36.886264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.875257Z","title":"Large language models-guided dynamic adaptation for temporal knowledge graph reasoning,","venue":null,"work_id":"b32ede61-befd-469f-a424-314d19cc0db0","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.495052Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:d8c9e5c541a8f161ae741613d6041d6af73af0d7663fb01b76dec7c9b6f416d6","observation_id":"b4ff183a-d54f-4d25-850d-ed5573b55c0d","resolution":{"observed_at":"2026-08-06T16:09:36.878657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:27.581444Z","title":"Y AGO 4.5: A large and clean knowledge base with a rich taxonomy,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.581444Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:6c4d36c86fc69d6e1b877a5169e6e67a3b0948dfaa60dcb170bf0c887e291eb1","observation_id":"2a71a20d-6e19-4895-b548-a6262f895052","resolution":{"observed_at":"2026-08-06T16:09:27.581444Z","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":"2026-08-06T16:09:36.866974Z","title":"Yago: a core of semantic knowledge,","venue":null,"work_id":"6788235c-6fc0-4b68-89b2-b90e967f4cac","year":2007},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.649354Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:36cea6b12ff716a26e7c74b1707a34f302cf4caa26900923c974c8792e79749f","observation_id":"6ce3fd05-9bdc-4d1b-8d55-ef37418b73ae","resolution":{"observed_at":"2026-08-06T16:09:36.869604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:27.757759Z","title":"Tackling sparse facts for temporal knowledge graph completion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.757759Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:9dd265d66630508bdc29c1e62725cd8a5bfb4c9d42d1d8b0cd75a6d20152182b","observation_id":"b1f18e8e-e721-4f6e-bac8-baf10d3d8097","resolution":{"observed_at":"2026-08-06T16:09:27.757759Z","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":"2026-08-06T16:09:36.859077Z","title":"Benchmarking challenges for temporal knowledge graph alignment,","venue":null,"work_id":"f326f29c-b744-4908-973c-f028cf5e2bd1","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.865478Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:72fe5cbec147e93fc4fb4cb93ecfb84ee2a9d8654d901584b3f2e66c5a50042c","observation_id":"dcf8c23d-2903-41a6-9f4e-1cd16d377482","resolution":{"observed_at":"2026-08-06T16:09:36.861936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.851535Z","title":"Unlocking the power of large language models for entity alignment,","venue":null,"work_id":"0a769a70-013d-49bc-ab72-a73ad8edef63","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:27.959649Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:6deffd41ee33eff559972cff3c5312c8cc33db0191fe81824eb82a70b0165c7d","observation_id":"dea94ddc-12cf-432c-ac5d-d577ced16d0d","resolution":{"observed_at":"2026-08-06T16:09:36.854091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.843341Z","title":"Introducing wikidata to the linked data web,","venue":null,"work_id":"35468f6f-46d8-4bae-9aa1-a5939a3d4cc1","year":2014},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.033783Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:88e94bdbac7feeba112f524b75477a42fe007d3d89b5699ceb2efa7e7e9df591","observation_id":"302d04a6-8a0f-4770-a4ec-0e1395e7c35d","resolution":{"observed_at":"2026-08-06T16:09:36.846481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:28.258061Z","title":"Towards semantic consistency: Dirichlet energy driven robust multi-modal entity alignment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.258061Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:31179092e039feada7ef9e7149b6e3f96b6d140dd0a224f9ef313de1485294fe","observation_id":"e0105c28-3deb-4b6e-ae0b-218eb182245d","resolution":{"observed_at":"2026-08-06T16:09:28.258061Z","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":"2026-08-06T16:09:36.835319Z","title":"An experimental study of state-of-the-art entity alignment approaches,","venue":null,"work_id":"6d19df05-7f97-446e-8805-82ccb030e7cf","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.371726Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:0835cd3d4a165bc77c379e4a2c6be2e217732f4c7616570997d08fb96a5fc595","observation_id":"ad8b21d6-35b2-4e8a-b530-ead3f997900f","resolution":{"observed_at":"2026-08-06T16:09:36.838134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-981-99-4250-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:35.089749Z","title":null,"venue":null,"work_id":"f355443d-4c06-4e1f-abff-c3b1a90745c7","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.454586Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:3077483f8be0e32e861fe0d6710a8f6cfd46bfc902e4dd2db300e45bfa112677","observation_id":"b7b44c0f-e67a-44ea-92ef-c3a9f41cc7b9","resolution":{"observed_at":"2026-08-06T16:09:35.092779Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.826514Z","title":"A benchmarking study of embedding-based entity alignment for knowledge graphs,","venue":null,"work_id":"17562bc3-edba-4c30-8ff4-17b769458cdf","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.548083Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:0b09eb7731dc9a3c55f32be404e8342c5f22a9d6996dada52ff678a51393ebce","observation_id":"6c2aa814-6f2c-408b-8060-91a37cafdaad","resolution":{"observed_at":"2026-08-06T16:09:36.829567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.818652Z","title":"Entity and relation matching consensus for entity alignment,","venue":null,"work_id":"4c1ebf99-0c54-41d0-8915-15b59a07aa0a","year":2021},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.639814Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:f9cc17f3e9e996c6445e25dcf5c1901086d47e8ea7efd159897eb83ae944931a","observation_id":"99a4fd49-5c72-4d4e-b404-425f9d1d1a90","resolution":{"observed_at":"2026-08-06T16:09:36.821363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.810658Z","title":"A benchmark and comprehensive survey on knowledge graph entity alignment via representation learning,","venue":null,"work_id":"e280a57b-2994-470f-9949-62ba3e2a6cd7","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.710003Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:be73584fe8697cbf8b00069ba7a0b0496e3a8eded84ecad7474a2f81d59e334d","observation_id":"897d46d3-00e4-4a77-bdeb-5e8b9cee9a72","resolution":{"observed_at":"2026-08-06T16:09:36.813657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:28.858416Z","title":"HLMEA: unsupervised entity alignment based on hybrid language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.858416Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:353f42bf2eb5842dc22b9f9a4d3e8799efd498863989b6aa7bd6db920f414131","observation_id":"24b735b2-2866-4d26-afcb-c05a3f0b4797","resolution":{"observed_at":"2026-08-06T16:09:28.858416Z","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":"2025.35555","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:35.914267Z","title":"SE-GNN: seed expanded-aware graph neural network with iterative optimization for semi-supervised entity alignment,","venue":null,"work_id":"57066694-51dd-4795-8c18-33940c78eeba","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:28.972395Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:872c425ebe83fbad92ac57b99e04c36d6dee2f01d01a4bafefbdaf9d12b46bf6","observation_id":"74fdc554-6b6e-4782-999a-f17c2047c6dc","resolution":{"observed_at":"2026-08-06T16:09:35.918872Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1551.37035","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:36.343766Z","title":"Unsupervised robust cross-lingual entity alignment via neighbor triple matching with entity and relation texts,","venue":null,"work_id":"ea0d0343-7c52-4199-b1b1-81dc04556447","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.091602Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:f3a317bbc7ff45155203885413f870caeda89feade4847cc0012e0233f8a42ef","observation_id":"c5cb7a17-54f7-4564-9614-8bce9b0b7e2b","resolution":{"observed_at":"2026-08-06T16:09:36.348311Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.802888Z","title":"Multilingual knowledge graph embeddings for cross-lingual knowledge alignment,","venue":null,"work_id":"7a3d9526-5db5-4d6c-99d4-05986a2606c8","year":2017},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.271296Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:bbe7783f0d9471477165eee962db326088c80721242c1eaf78278c931552ad4a","observation_id":"c10feb36-95c9-468e-acc8-0a3e64a204ff","resolution":{"observed_at":"2026-08-06T16:09:36.805588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.795042Z","title":"Bootstrapping entity alignment with knowledge graph embedding,","venue":null,"work_id":"ab287b9c-ecf2-4a9d-b81e-d182cef0b0d6","year":2018},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.435111Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:ad1350d8d53c8140610c66cc099f992ca82a272ce079dc293eede118420e1648","observation_id":"916a3b63-c8b0-4b25-a3dd-6f17596ce5c4","resolution":{"observed_at":"2026-08-06T16:09:36.797965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.787484Z","title":"Translating embeddings for modeling multi-relational data,","venue":null,"work_id":"7917d1f1-d885-4d49-bbb8-8c99d57a8a0d","year":2013},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.562018Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:e1e58cfd4243d60c0822cfb2529b17b61dec59797f41fb900a4d300c72bec04e","observation_id":"a4617cc8-f0b5-4849-a75c-220e3c04df7b","resolution":{"observed_at":"2026-08-06T16:09:36.790048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02862","last_updated":"2025-03-26T17:44:17Z","snapshot_observed_at":"2026-08-03T01:37:15.995323Z","submitted_at":"2024-07-03T07:22:20Z","title":"HybEA: Hybrid Models for Entity Alignment","version":2},"cited_work":{"arxiv_id":"2407.02862","doi":"10.48550/arxiv.2407.02862","metadata_source":"pith","pith_arxiv_id":"2407.02862","snapshot_observed_at":"2026-08-06T18:16:30.548575Z","title":"HybEA: Hybrid Models for Entity Alignment","venue":"cs.DB","work_id":"afe9d743-c4e6-4b84-b2f9-f1254156bfc4","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.716231Z"},"links":{"cited_paper":"/paper/2407.02862","citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:3f9133d8388f98ccd2100e780fea80d42ac43b46802a9a32a4c3f4751f42f303","observation_id":"ee040914-d70d-4e27-8dd5-fb0f095f6215","resolution":{"observed_at":"2026-08-06T16:09:35.078049Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.779027Z","title":"A benchmarking study of embedding-based entity alignment for knowledge graphs,","venue":null,"work_id":"09586f94-e381-4e09-a890-95b4859e0e58","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.868701Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:d0f0685d8fe5625960e66b97b1ae5e3a49a8847faa5c9877e357b173a9a746e4","observation_id":"171a22dc-cd79-4de9-94d8-1dfab0b62fea","resolution":{"observed_at":"2026-08-06T16:09:36.782256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.771098Z","title":"Cross-lingual entity alignment via joint attribute-preserving embedding,","venue":null,"work_id":"86eb337f-7268-40fa-846f-d8b8a6f9ffdd","year":2017},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:29.947996Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:fbdbaea7d068cbadc427d8a83b1e66083dcf469570d26b28eba7a42be47c7dfb","observation_id":"a8a6febf-d451-4ac8-a822-917c619a4bb2","resolution":{"observed_at":"2026-08-06T16:09:36.773835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.762751Z","title":"Make it easy: An effective end-to-end entity alignment framework,","venue":null,"work_id":"5440b441-c085-4271-9365-3f75a9e33a8e","year":2021},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.031921Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:96afae520eada0d98a4418f3641bb75d4b2557a3af9e61a6596abe7539c6b083","observation_id":"692c6c2e-f3f4-410a-b950-ac0c9f108e98","resolution":{"observed_at":"2026-08-06T16:09:36.766125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.754205Z","title":"Cross-lingual knowledge graph alignment via graph convolutional networks,","venue":null,"work_id":"ca01d1ac-392c-4798-b972-d499ec96c6e3","year":2018},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.095481Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:ad4ee11a5e03b494ddc2f9526564c2e0f29f61f3201fe4ef3425c30314b5aff2","observation_id":"3039774f-e4d5-41f1-ab54-d6ed59746f5b","resolution":{"observed_at":"2026-08-06T16:09:36.757161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.745772Z","title":"Integrating manifold knowledge for global entity linking with heterogeneous graphs,","venue":null,"work_id":"6cef3375-7d0d-40b7-a191-2798d9c7e656","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.183757Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:dab6c76527f5c52ead8d1b79e396f99ebe2f740c0f5527406085876adb020ca6","observation_id":"14b3fdfe-bf38-461c-9b5f-cc9165b77b2d","resolution":{"observed_at":"2026-08-06T16:09:36.749270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.737539Z","title":"Boosting the speed of entity alignment 10 ×: Dual attention matching network with normalized hard sample mining,","venue":null,"work_id":"ee400b8a-bf2a-4228-b81e-2e6dff2763ed","year":2021},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.239599Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:90e64c25b37d0963765b147312843e331ac14b4cbfb16f0a1d7374d1d4a66858","observation_id":"b1d36d4c-dcde-4332-bda4-7b791379e162","resolution":{"observed_at":"2026-08-06T16:09:36.740318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.729749Z","title":"MRAEA: an efficient and robust entity alignment approach for cross-lingual knowledge graph,","venue":null,"work_id":"4d9169c5-39fb-4692-bae7-e002761117d8","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.322617Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:a9f518f05fa3a3fb4c702132ea0b64a3b440b60623cf0f8ee149fb900b11686c","observation_id":"8c01de9d-63a7-4762-86e9-949ffab63dad","resolution":{"observed_at":"2026-08-06T16:09:36.732307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.721967Z","title":"Relational reflection entity alignment,","venue":null,"work_id":"28945424-f900-485e-8e19-1ab28b51f427","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.416487Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:5716bfc85c5d375bfcc58b76770811e40bd32c99d8deffa1c0a3b05676959e6e","observation_id":"150dee57-50e0-41d6-933d-17af273dc01c","resolution":{"observed_at":"2026-08-06T16:09:36.724790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:30.514377Z","title":"FuAlign: Cross-lingual entity alignment via multi-view representation learning of fused knowledge graphs,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.514377Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:2ddc08605f0191ebbe23a58c112833447709a4d97ce76a40c45aed785fbac6bc","observation_id":"8f297443-341c-4ec1-9f2e-e1c0822f8e35","resolution":{"observed_at":"2026-08-06T16:09:30.514377Z","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":"2026-08-06T16:09:30.553724Z","title":"BERT-INT: A bert-based interaction model for knowledge graph alignment,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.553724Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:b2c4e289c742d72f16df4ae7ff6aa776c5ab1c714fe3d2bd05013e778415a8fd","observation_id":"33dd4ca0-6b45-4ac1-91e5-e93519c1dfc6","resolution":{"observed_at":"2026-08-06T16:09:30.553724Z","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":"2026-08-06T16:09:36.714098Z","title":"Entity alignment with noisy annotations from large language models,","venue":null,"work_id":"a6b5e5c2-1dd8-4577-8621-acc8bf2d2dc9","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.615435Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:6f30aedcc856be7a71245379efe8c95219725f41bb85964ab3dba55af18c1ffc","observation_id":"2e5f3aa6-0402-4e90-a428-141bb5b4eefc","resolution":{"observed_at":"2026-08-06T16:09:36.717050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.16960","last_updated":"2024-01-30T12:41:04Z","snapshot_observed_at":"2026-08-07T06:22:15.284778Z","submitted_at":"2024-01-30T12:41:04Z","title":"Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.16960","snapshot_observed_at":"2026-08-06T16:09:30.677946Z","title":"Two heads are better than one: Integrating knowledge from knowledge graphs and large language models for entity alignment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.677946Z"},"links":{"cited_paper":"/paper/2401.16960","citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:f49545dd9d5092aaa738c2f7b5a8f63badbcf2104125c551b31401fbeaa6aeea","observation_id":"b5ad49ff-bd5b-48b3-b1d4-4041e27b7574","resolution":{"observed_at":"2026-08-06T16:09:30.677946Z","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":"2026-08-06T16:09:36.706616Z","title":"BERT: Pre-training of deep bidirectional transformers for language understanding,","venue":null,"work_id":"f247d32f-c8ec-4c72-881a-5c2a73da7018","year":2019},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.747396Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:ad0da6976b747995e986e45c8ef393625203ea945fe11c26acdad9cc84e9d0c1","observation_id":"59d4f2ca-7395-4ee0-a518-a7cdd92dc354","resolution":{"observed_at":"2026-08-06T16:09:36.709154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.698891Z","title":"Paris: Probabilistic alignment of relations, instances, and schema,","venue":null,"work_id":"acaca1da-cf77-49b9-8445-49adc05055fb","year":2011},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.820082Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:fe572de9c6233f7590d6b19cc8800674c0f97f63d9ea9f9b781d516198978107","observation_id":"903b6fbd-892c-4281-b68b-86008ed254ea","resolution":{"observed_at":"2026-08-06T16:09:36.701414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.690926Z","title":"Matching knowledge graphs in entity embedding spaces: An experimental study,","venue":null,"work_id":"0fdb315b-4d22-4174-a88a-f648df4b8ea6","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.901096Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:cb5d428a75c71a5b8fb7f8fbbbcb853230d133dfd3b61b45dfa1826e1c80d20b","observation_id":"ff2ed244-a055-41c2-94a6-acc543f36419","resolution":{"observed_at":"2026-08-06T16:09:36.693465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:30.993535Z","title":"Collective entity alignment via adaptive features,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:30.993535Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:139b59dee40261f6dfc34ae624c445b1f25b78bf3af4402aa0e42b45cc87e83b","observation_id":"9c2e7066-6678-47fd-bef8-c459c8af2c3d","resolution":{"observed_at":"2026-08-06T16:09:30.993535Z","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":"2026-08-06T16:09:36.683344Z","title":"High-quality task division for large-scale entity alignment,","venue":null,"work_id":"b00690ca-4178-4c63-8751-0e32a88cb366","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.078016Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:8202f722b993b3e4a2b988af64ff342c7c4603500666c21b66edf53a9cdd7358","observation_id":"ea0f3c6b-db4b-4a76-b686-5b18f24ab6b3","resolution":{"observed_at":"2026-08-06T16:09:36.686012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.674938Z","title":"Clusterea: Scalable entity alignment with stochastic training and normalized mini-batch similarities,","venue":null,"work_id":"51ff6e83-ccc4-4a6b-85af-ce0f86e66f68","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.154288Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:2fa9f9b35dd4e6efd43310b94fbfac8bc952d242d74d6f3a6d52155c94ce123f","observation_id":"d9ffc050-c84a-4222-8633-af280f8eac8b","resolution":{"observed_at":"2026-08-06T16:09:36.677714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00778-021-00703-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:34.831464Z","title":"On entity alignment at scale,","venue":null,"work_id":"d1889fc7-3e3b-434e-bf04-891cdafb5634","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.229071Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:dbbe9734289e38bc91bc553a72c802702cd0265ddfe208f3b6b7ba779910115b","observation_id":"0a7fcfa6-f6b7-4d5b-ab57-e6668eae8d3e","resolution":{"observed_at":"2026-08-06T16:09:34.912439Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.665886Z","title":"Reinforced active entity alignment,","venue":null,"work_id":"0ab9e73e-e624-441f-8126-8591f1177394","year":2021},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.299045Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:16a3cfa0cfaf3007dd74b65cb3013f452d5432a057786352eb1afcac67f44a43","observation_id":"332273f9-6461-4cd3-855d-b0614f1b094b","resolution":{"observed_at":"2026-08-06T16:09:36.669166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.657753Z","title":"Interactive contrastive learning for self-supervised entity alignment,","venue":null,"work_id":"f30a1cb3-d280-40df-b2e9-9ad48d86d4ba","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.375600Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:4d5193dad4dbe6447333f1e275544b3d7600ff073b8f42e44d8d37f174c9f906","observation_id":"efb5a310-adff-4eaf-b3d0-39ceb16934d8","resolution":{"observed_at":"2026-08-06T16:09:36.660973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2025.10718","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:35.777880Z","title":"Leveraging neighborhood distance awareness for entity alignment in temporal knowledge graphs,","venue":null,"work_id":"bd682438-0e3c-45e2-bc92-5acc05c24f2e","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.467268Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:961d8a8539389d18fec8c2fc572df41525509273ef16497c12b795c3627ca9a9","observation_id":"74023ddf-0c73-477d-be80-14bd33fc5332","resolution":{"observed_at":"2026-08-06T16:09:35.782832Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.10614","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:35.692564Z","title":"Embedding- based entity alignment of cross-lingual temporal knowledge graphs,","venue":null,"work_id":"43d366b2-8490-48d5-9edc-54598ce80324","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.538892Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:7f0a9a7e206eb0bf41deb9d178eac4d2f93847f7dac5d1bbefb69bf885f88b38","observation_id":"c8f1f5cc-576d-4bae-af7b-0c05626645db","resolution":{"observed_at":"2026-08-06T16:09:35.698842Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.648978Z","title":"A relation enhanced model for temporal knowledge graph alignment,","venue":null,"work_id":"5575133d-1383-4ab7-a587-2adafa7b8548","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.629428Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:826298c5a2801e8a382273945638253d1b7be16a0de49201903278ccc19c76c8","observation_id":"e48ce104-cc93-4e5e-9b41-1fa8b29206f4","resolution":{"observed_at":"2026-08-06T16:09:36.652351Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.640949Z","title":"TEA: time-aware entity alignment in knowledge graphs,","venue":null,"work_id":"fe23bf68-e904-4585-9947-fdf1eac690ca","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.721983Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:0e765604971ac3d012fede9d0a5a2dd4ba43a94791ceddd659680945a244d94e","observation_id":"ccfbe816-38ec-4002-b945-c9f28017d70d","resolution":{"observed_at":"2026-08-06T16:09:36.643984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:31.882386Z","title":"T2TD: text-3d generation model based on prior knowledge guidance,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.882386Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:9fcc501177c5dd0754aaf17fc259901cb9ffe1462a0a60b517132c966407c771","observation_id":"3f098cec-2b95-45a7-8f55-63a77d0725c3","resolution":{"observed_at":"2026-08-06T16:09:31.882386Z","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":"2026-08-06T16:09:36.622197Z","title":"Self-rag: Learning to retrieve, generate, and critique through self-reflection,","venue":null,"work_id":"f879bc8e-7a78-4263-b720-725f5f4343b3","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.955631Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:1d6b9c0393a80530268d332f46160a35597473689172f1f4cb9178dc592e09b1","observation_id":"98035b4a-eff1-4dbf-9f45-35b11c590905","resolution":{"observed_at":"2026-08-06T16:09:36.625767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:32.001828Z","title":"A survey of graph retrieval-augmented generation for customized large language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.001828Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:73e4611ae14a24e92015c39c01a91a370d9775ad8b3a455661c5eb35f01e7599","observation_id":"ab8fe927-b715-4e9e-9581-39a29cda8634","resolution":{"observed_at":"2026-08-06T16:09:32.001828Z","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":"2026-08-06T16:09:36.614211Z","title":"Retrieval augmented language model pre-training,","venue":null,"work_id":"c66e4363-657a-4948-a524-147173d39fd9","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.089215Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:4d3942a5e284d3ad2208d43907dba98e17c635cc88f7f2302a6d657957a01632","observation_id":"ccd07b42-9f16-410d-8d52-79520ab2d17d","resolution":{"observed_at":"2026-08-06T16:09:36.617062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.598129Z","title":"Unsupervised dense information retrieval with contrastive learning,","venue":null,"work_id":"e34c613c-1299-4bea-8651-88d3d33b25db","year":2022},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.244893Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:d7d1b00f7631097070f858fbe26ca565bea8e741a82b78082959df4403b3eacf","observation_id":"335f5e4c-1576-4710-a780-01668c9056ce","resolution":{"observed_at":"2026-08-06T16:09:36.600731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai.v39i24.34809","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:34.594200Z","title":"Radio: Real-time hallucination detection with contextual index optimized query formulation for dynamic retrieval augmented generation,","venue":null,"work_id":"4dc32225-fa1e-45f7-8344-e47d30275583","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.331645Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:9e9d49d480f91163b5439578cdccd472fc135dc5e61e177a049620bc2963d044","observation_id":"35b37682-69aa-48ac-b864-177bcd917283","resolution":{"observed_at":"2026-08-06T16:09:34.669376Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:32.455917Z","title":"Understand what LLM needs: Dual preference alignment for retrieval-augmented generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.455917Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:5b61257fd0f3d5a22b5d140dbd7872da48afd0d1eda19ed16c278d0349579e3d","observation_id":"b50b9fa1-75de-494e-b73b-1bdb883f9239","resolution":{"observed_at":"2026-08-06T16:09:32.455917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.14484","last_updated":"2024-08-18T11:47:55Z","snapshot_observed_at":"2026-07-06T19:06:10.813371Z","submitted_at":"2024-08-18T11:47:55Z","title":"Agentic Retrieval-Augmented Generation for Time Series Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.14484","snapshot_observed_at":"2026-08-06T16:09:32.522547Z","title":"Agentic retrieval-augmented generation for time series analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.522547Z"},"links":{"cited_paper":"/paper/2408.14484","citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:cc10a7f8d5842c4de2eea3f719d1487c85d03cc36d624c911b3fbdc1365273ef","observation_id":"37719bc8-45a8-4849-9c2c-a6088f407a18","resolution":{"observed_at":"2026-08-06T16:09:32.522547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.09823","last_updated":"2025-04-14T02:47:23Z","snapshot_observed_at":"2026-08-07T16:06:03.524881Z","submitted_at":"2025-04-14T02:47:23Z","title":"RAKG:Document-level Retrieval Augmented Knowledge Graph Construction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.09823","snapshot_observed_at":"2026-08-06T16:09:32.606106Z","title":"Rakg: Document-level retrieval augmented knowledge graph construc- tion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.606106Z"},"links":{"cited_paper":"/paper/2504.09823","citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:bbbd46b21e403365bfab5e2c14d91d8c117fb418cacd3275610dba56bb6a537e","observation_id":"22360841-9de5-4a85-a927-b2dfd7a8c172","resolution":{"observed_at":"2026-08-06T16:09:32.606106Z","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":"2024.34327","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:09:35.453892Z","title":"Learning to cut via hierarchical sequence/set model for efficient mixed-integer programming,","venue":null,"work_id":"f3ee138b-0ebe-4ddf-8919-abeabe597e33","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.704535Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:b45a84cb0c3919b7ee4ccf60d639b90ebf3b918c38ec8bceb9729be18527e10f","observation_id":"3bf3c99b-b28f-4d52-ab36-e57d9ee5b509","resolution":{"observed_at":"2026-08-06T16:09:35.461178Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.590024Z","title":"Retrieval-augmented generation for large language model based few-shot chinese spell checking,","venue":null,"work_id":"f20c7897-f263-4ef4-ac87-b381e3cb08f6","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.801078Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:54c4b09c71848242584db0fc5ec4648f77909da0e03d5d5be3d83edcce93417c","observation_id":"195c9beb-2d3f-4046-ae89-22bbd3c49f83","resolution":{"observed_at":"2026-08-06T16:09:36.592690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.581955Z","title":"Self-consistency improves chain of thought reasoning in language models,","venue":null,"work_id":"2414a3fa-a168-4a9f-901f-6e82096dba05","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.900054Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:f7a8861a01fc18e65ded80e99e199a247e260bdb43e42604517828315b170e64","observation_id":"8ef67265-559c-45e3-b6ad-542b246479d0","resolution":{"observed_at":"2026-08-06T16:09:36.584820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:32.969729Z","title":"Query rewriting in retrieval-augmented large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.969729Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:fd973f789f531781e17b63a786cb67c461fdfc897a2b89cc339af14b54ce2048","observation_id":"4112e59c-c680-4145-ac8b-ff2480df0e53","resolution":{"observed_at":"2026-08-06T16:09:32.969729Z","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":"2026-08-06T16:09:36.573693Z","title":"Speculative RAG: enhancing retrieval augmented generation through drafting,","venue":null,"work_id":"7dece9ed-d983-42a4-87c8-72222c05b304","year":2025},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.046998Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:cc192b77e6c7bc63b70880a0e47201389b29922508da062e248384ba77f15b46","observation_id":"1a62e665-85b3-478e-bb3e-a08317043999","resolution":{"observed_at":"2026-08-06T16:09:36.576662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:33.125225Z","title":"Retrieval-augmented hypergraph for multimodal social media popularity prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.125225Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:a444a88561a6721d3d2b0885aa93461a516c77d976759efda36e79595508257d","observation_id":"079f2d33-edd3-48d7-a26d-c7c2011cc9f0","resolution":{"observed_at":"2026-08-06T16:09:33.125225Z","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":"2026-08-06T16:09:36.565166Z","title":"Tensor decompositions for temporal knowledge base completion,","venue":null,"work_id":"b6d6cbb2-374b-4c56-a959-37d22f4ea3cc","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.236403Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:93798842f9442a7e325dd98f2f46630508737646a4f584af95cd62ca4a0b9144","observation_id":"2b3970a9-f80d-4c02-a82b-337c00f73b05","resolution":{"observed_at":"2026-08-06T16:09:36.568066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:33.315851Z","title":"Diachronic embedding for temporal knowledge graph completion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.315851Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:84f5b3c745d3f32727ebd6d66c4ee459aec78a4152415d80dcd56a3c3a9d3fb1","observation_id":"eb6a995c-6c13-4d76-b75a-2e618e9f77f4","resolution":{"observed_at":"2026-08-06T16:09:33.315851Z","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":"2026-08-06T16:09:36.555900Z","title":"Word translation without parallel data,","venue":null,"work_id":"33928dce-5f0e-4d98-968a-e3c538a95702","year":2018},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.443575Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:215dbbc0686761a1b2792914621c2d19afc7b91f550e1ce8d2e2e7b859e086f0","observation_id":"2e9945b7-c77b-4f90-9b21-019742283ad9","resolution":{"observed_at":"2026-08-06T16:09:36.559204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:33.530820Z","title":"Temporal knowledge question answering via abstract reasoning induction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.530820Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:5bfb69126409cb06b71c3b365b688d20e0cbd93692ccd2517649aaa1b346593b","observation_id":"515a2f61-68fe-470d-a18e-1fc41992b949","resolution":{"observed_at":"2026-08-06T16:09:33.530820Z","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":"2026-08-06T16:09:36.546050Z","title":"Timemixer: Decomposable multiscale mixing for time series forecasting,","venue":null,"work_id":"6339d174-8674-461d-89a9-be352a57d565","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.652334Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:2bd9320461bb2c241182222f785f36e1961f1acfa2f0332360ab065b5fc84a7c","observation_id":"3bc6f9ca-f520-48ad-9fa3-e36ac8b1e13d","resolution":{"observed_at":"2026-08-06T16:09:36.548830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.535774Z","title":"Ada-mshyper: Adaptive multi- scale hypergraph transformer for time series forecasting,","venue":null,"work_id":"7bc6dee8-9f69-4bd3-99cb-73e7d88d3c99","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.759719Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:01d90f2dfe362cc436255f10f2f7f6e72ae937281b50f43f713a01f169e1739c","observation_id":"58626b6b-1d1a-465e-8173-f9510012bc13","resolution":{"observed_at":"2026-08-06T16:09:36.539122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:34.029660Z","title":"Self-alignment for factuality: Mitigating hallucinations in llms via self-evaluation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:34.029660Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:f95ccea97f3d7ffe35ce4039b329b097b7fc4441f9fc0ca048f6afc91bee5cf5","observation_id":"1243caab-5c80-413e-a0a8-45f9de964bf0","resolution":{"observed_at":"2026-08-06T16:09:34.029660Z","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":"2026-08-06T16:09:34.105527Z","title":"Unifying large language models and knowledge graphs: A roadmap,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:34.105527Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:701c3e98f3a45b246d1f896a0e0e75e9f61abce302b8d70cffabc78628d401eb","observation_id":"5d039d18-9813-4a9b-a234-02ad69781602","resolution":{"observed_at":"2026-08-06T16:09:34.105527Z","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":"2026-08-06T16:09:34.224562Z","title":"Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:34.224562Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:c17200e2792ffa3443a9d247e9efb9136c9279380173a9bd8d17f22a88d238da","observation_id":"eb639f22-61c8-482e-99c3-d52cfcfa738c","resolution":{"observed_at":"2026-08-06T16:09:34.224562Z","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":"2026-08-06T16:09:34.377982Z","title":"VTQA: visual text question answering via entity alignment and cross-media reasoning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:34.377982Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:6c006a2ce3370d2514fcf3160098fc90097a4cd3487f4e60d4eb030af9f29a94","observation_id":"4e3ab5ef-2585-4eff-9668-af803cc54316","resolution":{"observed_at":"2026-08-06T16:09:34.377982Z","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":"2026-08-06T16:09:36.606364Z","title":"3929–3938","venue":null,"work_id":"399c6512-372c-4371-a2c7-fa1cf5a3b39e","year":2020},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":119,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:32.183494Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:4e955bad211535bf1ac4df99fe3b8b1c7f64fa15ddeda33e14a33d4082c16a09","observation_id":"6f4b2473-c7e0-4a7b-a4ca-2ba9e15231a2","resolution":{"observed_at":"2026-08-06T16:09:36.608865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.632007Z","title":"2591–2599","venue":null,"work_id":"87817803-ec38-4a87-9732-840f88bf6c1b","year":2023},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:31.816226Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:baea9112ed1df92c949644517db28911ad5fb5a622314bd679a76477b373bb51","observation_id":"eb18320c-03c6-4eec-bcd1-1e5f0661c051","resolution":{"observed_at":"2026-08-06T16:09:36.635281Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:09:36.527227Z","title":"Available: http://papers.nips.cc/paper files/paper/2024/ hash/3a6935d11910d6f9142b0a1e36fc6753-Abstract-Conference.html","venue":null,"work_id":"5e885c78-57fe-496c-9bfc-ac637d263778","year":2024},"citing_paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:33.883026Z"},"links":{"citing_paper":"/paper/2507.14475"},"observation_digest":"sha256:80ed817666ef06245e0c56069029159ab7e4ac84288d604069a6daf0449dd551","observation_id":"67dcd2f5-586c-4ecc-b07f-fbe01dbb4927","resolution":{"observed_at":"2026-08-06T16:09:36.530416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.14475","last_updated":"2025-07-19T04:12:06Z","latest_version":1,"primary_category":"cs.DB","snapshot_observed_at":"2026-08-06T21:36:27.866339Z","submitted_at":"2025-07-19T04:12:06Z","title":"Towards Temporal Knowledge Graph Alignment in the Wild"},"reference_resolution":{"displayed":84,"state_counts":{"malformed_identifier":1,"metadata_mismatch":7,"parse_uncertain":1,"unresolved":26,"verified_exact":5,"verified_fuzzy":44},"total_outbound_references":84},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 1 inbound Pith citation observation for arXiv:2507.14475."}