{"as_of":"2026-08-08T11:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f7689d71f6599d229974a84026f5252df59c8da236aa0b92f7bd3eb6474c5518","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:04:06.929115Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.03947/citation-record","integrity":"/paper/2507.03947/integrity","json":"/paper/2507.03947/citation-record.json","paper":"/paper/2507.03947"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1409.0473","last_updated":"2016-05-19T21:53:22Z","snapshot_observed_at":"2026-07-06T03:53:10.336430Z","submitted_at":"2014-09-01T16:33:02Z","title":"Neural Machine Translation by Jointly Learning to Align and Translate","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.0473","snapshot_observed_at":"2026-08-06T20:04:01.357849Z","title":"Neural machine translation by jointly learning to align and translate","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.357849Z"},"links":{"cited_paper":"/paper/1409.0473","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:a1ab3d5b223e161dd80942729b949b5ca6663d425bb1414e29621fcc06a9213f","observation_id":"845dbd86-518b-4c75-9f32-5c30e0f7c351","resolution":{"observed_at":"2026-08-06T20:04:01.357849Z","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":"2026-08-06T20:04:13.864071Z","title":"Video suggestion and discovery for youtube: taking random walks through the view graph","venue":null,"work_id":"4fce881a-06eb-4a11-b135-2c8baf324c6f","year":2008},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.492790Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:8f3bba79723ac095b830e7396722775e4f9b4ba176bfde7f7e2b78256836930e","observation_id":"2bfe5b38-ee85-4557-9aa8-2c7399e52687","resolution":{"observed_at":"2026-08-06T20:04:13.921746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.00816","last_updated":"2018-06-01T13:18:29Z","snapshot_observed_at":"2026-07-06T06:26:15.665895Z","submitted_at":"2018-03-02T11:49:32Z","title":"NetGAN: Generating Graphs via Random Walks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.00816","snapshot_observed_at":"2026-08-06T20:04:01.597720Z","title":"Netgan: Generating graphs via random walks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.597720Z"},"links":{"cited_paper":"/paper/1803.00816","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:87285ba3fe315ade88554f4527ff35a1bc6d2673e882fc3989dcac323864afe5","observation_id":"cc84f3a8-8cd3-4509-b47f-e7c4e35f4689","resolution":{"observed_at":"2026-08-06T20:04:01.597720Z","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":"2026-08-06T20:04:13.698146Z","title":"Translating embeddings for modeling multi-relational data","venue":null,"work_id":"78131b7f-ab36-4e9d-9e6c-c53dab3db03f","year":2013},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.713192Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:9016562d54e6e67f679987934edd9d1cfd959d20489e85e63d7dc4e05661f27f","observation_id":"b85d79d8-d498-42ec-b4eb-32c1146a2dac","resolution":{"observed_at":"2026-08-06T20:04:13.771638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:13.524488Z","title":"A comprehensive survey of graph embedding: Prob- lems, techniques, and applications","venue":null,"work_id":"d0e78645-bae9-487b-841b-52f79c443d22","year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.831733Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:73c58457f7414eee773ccdb4f5a2b31e7b04e62db6c93dbfcc0770077f36366b","observation_id":"2a5d4dc8-6af4-4b08-9d34-d7e1f96f9fe2","resolution":{"observed_at":"2026-08-06T20:04:13.595499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:13.370459Z","title":"Grarep: Learning graph representations with global structural information","venue":null,"work_id":"dacee8dd-55d5-4eff-a2a0-ba051d1f0f04","year":null},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.962001Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:aa699bfd364aad1358c2985efb619c69b6247e4dde124a15945a0d30022b6aff","observation_id":"14fea2b0-7ac0-475d-b888-f0553bddf2a3","resolution":{"observed_at":"2026-08-06T20:04:13.454323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.03584","last_updated":"2020-01-10T09:06:09Z","snapshot_observed_at":"2026-07-06T08:35:42.709133Z","submitted_at":"2019-11-08T23:48:38Z","title":"On the Relationship between Self-Attention and Convolutional Layers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.03584","snapshot_observed_at":"2026-08-06T20:04:02.100755Z","title":"On the relationship between self-attention and convolutional layers","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.100755Z"},"links":{"cited_paper":"/paper/1911.03584","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:70210759fb4361071377670b0112f36896eeece025c14573b1c166f722f86786","observation_id":"9bbb0a99-a740-43d8-af83-abfb3903a314","resolution":{"observed_at":"2026-08-06T20:04:02.100755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.16362","last_updated":"2021-05-20T14:48:30Z","snapshot_observed_at":"2026-08-05T17:26:35.093147Z","submitted_at":"2020-06-29T20:28:52Z","title":"Multi-Head Attention: Collaborate Instead of Concatenate","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.16362","snapshot_observed_at":"2026-08-06T20:04:02.222947Z","title":"Multi-head attention: Collaborate instead of concatenate","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.222947Z"},"links":{"cited_paper":"/paper/2006.16362","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:eb36fa22683048587099b13827318dd7d630224efe39080f5f62145cc1410a5b","observation_id":"3217490d-0618-4117-b085-1b8e2a061a55","resolution":{"observed_at":"2026-08-06T20:04:02.222947Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.01476","last_updated":"2018-07-04T09:53:46Z","snapshot_observed_at":"2026-08-02T12:35:52.676931Z","submitted_at":"2017-07-05T17:18:17Z","title":"Convolutional 2D Knowledge Graph Embeddings","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.01476","snapshot_observed_at":"2026-08-06T20:04:02.341830Z","title":"Convolutional 2d knowledge graph embed- dings","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.341830Z"},"links":{"cited_paper":"/paper/1707.01476","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:50e4086a56ba4504c17be78e0656af3a1b385e33223e4d357951bf3e1abdb212","observation_id":"e2b4810e-0cdc-48d6-aaf5-e5f601a1214f","resolution":{"observed_at":"2026-08-06T20:04:02.341830Z","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":"2026-08-06T20:04:13.069657Z","title":"Convolutional 2d knowledge graph em- beddings","venue":null,"work_id":"9e58d307-189e-438c-b1bc-9cbcd5b9e0e0","year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.452808Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:83a1d0e458feb09e171c77595a1117a72b71ed2823144118c2b67e2051056298","observation_id":"5db983c9-d7e0-453b-a072-c032f9dd5cb7","resolution":{"observed_at":"2026-08-06T20:04:13.228431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:12.809350Z","title":"Fast rule mining in ontological knowledge bases with amie","venue":null,"work_id":"25f28d4a-1d77-4abd-9f33-ccd46a616147","year":2015},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.578912Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:c6b5bf26e9493fb6c4248eff58c0cb3fcc31a92e723d8a74809be10ae7c37be0","observation_id":"9aa745c3-f2d8-468e-9a71-930b9cee39d7","resolution":{"observed_at":"2026-08-06T20:04:12.916829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:12.589752Z","title":"Introducing the Knowledge Graph: things, not strings, 2020 (accessed on August 27, 2020)","venue":null,"work_id":"f373b83e-30fc-4f30-8f49-4bfd3809af9a","year":2020},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.709229Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:46799a55ced5663deb78eae544bc583fb2dee760839229e9c28075833d9412c1","observation_id":"ce13dca7-485f-4c5d-aa38-e23f397162ed","resolution":{"observed_at":"2026-08-06T20:04:12.703508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:12.383376Z","title":"Graph embedding tech- niques, applications, and performance: A survey","venue":null,"work_id":"ead2957b-217b-47e5-8431-320bb551ca44","year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.827326Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:870094aad9493b7b1382e39a7f6d421f7fc36e23ff38c58052c63f4fb45f7d68","observation_id":"6d07ac66-29e7-48ae-b273-4a275d1d723d","resolution":{"observed_at":"2026-08-06T20:04:12.453848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:12.113886Z","title":"node2vec: Scalable feature learning for networks","venue":null,"work_id":"b8f27e1f-9b11-4e21-9e0f-a6497b31a964","year":2016},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:02.939629Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:777169696359ded05f5f6afcee7ea18891e153f8050e50d92ba20e810901d14a","observation_id":"d3eaadcb-52d2-4f3a-8d97-9fc419de84ef","resolution":{"observed_at":"2026-08-06T20:04:12.204516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.04914","last_updated":"2019-05-13T08:53:31Z","snapshot_observed_at":"2026-07-06T07:52:32.758734Z","submitted_at":"2019-05-13T08:53:31Z","title":"Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs","version":1},"cited_work":{"arxiv_id":"1905.04914","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.04914","snapshot_observed_at":"2026-08-06T20:04:07.713857Z","title":"Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs","venue":"cs.AI","work_id":"6af674a1-5cb0-4816-b544-417c3fc403e1","year":2019},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.036858Z"},"links":{"cited_paper":"/paper/1905.04914","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:ab04b0e48c3b5087ff4154ae634f88da3b7b580301792f0f9d6ed69879231a13","observation_id":"57af573e-0117-40b1-9503-cb10ec44e4f2","resolution":{"observed_at":"2026-08-06T20:04:07.836575Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:11.841283Z","title":"Hopfield network","venue":null,"work_id":"b7e0387f-cdea-44bd-a2ca-462c3e21cb72","year":1977},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.126304Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:9e636dec5eb9c7cf043df810bd357533aa5fad0a68b41cdbe05033c77edb3024","observation_id":"8446f5d3-3e4d-4ce9-ba18-ad46d962d080","resolution":{"observed_at":"2026-08-06T20:04:11.947267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.11921","last_updated":"2018-06-08T09:31:56Z","snapshot_observed_at":"2026-08-03T19:35:07.537874Z","submitted_at":"2018-05-30T12:43:47Z","title":"Anonymous Walk Embeddings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.11921","snapshot_observed_at":"2026-08-06T20:04:03.274777Z","title":"Anonymous walk em- beddings","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.274777Z"},"links":{"cited_paper":"/paper/1805.11921","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:518fd9675a92eaa183b159462fa34ffb51c4d82550f0070b699260ea94eaf5cd","observation_id":"f026a8de-2aa1-4d2d-8bb2-da5ab013a4d2","resolution":{"observed_at":"2026-08-06T20:04:03.274777Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.00388","last_updated":"2021-04-01T05:48:44Z","snapshot_observed_at":"2026-08-04T19:28:14.015670Z","submitted_at":"2020-02-02T13:17:31Z","title":"A Survey on Knowledge Graphs: Representation, Acquisition and Applications","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.00388","snapshot_observed_at":"2026-08-06T20:04:03.430937Z","title":"A survey on knowledge graphs: Rep- resentation, acquisition and applications","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.430937Z"},"links":{"cited_paper":"/paper/2002.00388","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:1855570bb4db3b34bb524a5e1fb92677fafc999a19711a2ba4a0a8973b5ead2c","observation_id":"ac89735e-50f6-4402-aa95-fdc311a64f54","resolution":{"observed_at":"2026-08-06T20:04:03.430937Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-06T20:04:03.555418Z","title":"Semi-supervised classi- fication with graph convolutional networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.555418Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:1a4ae33e43647ef5dfdda6d9be8bb3bf774ff12a53fd053c13823c1121bc7b61","observation_id":"b43ea082-ddf7-476c-be41-4009ce919846","resolution":{"observed_at":"2026-08-06T20:04:03.555418Z","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":"2026-08-06T20:04:03.717934Z","title":"Object recognition with gradient-based learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.717934Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:fa3ee9f52f31110ba0eeeb0f92a48eb5433c3c09b40cca56db8b082c8992d203","observation_id":"340b58c9-ed6a-4cd5-9e7d-06ebb7593520","resolution":{"observed_at":"2026-08-06T20:04:03.717934Z","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":"2026-08-06T20:04:11.596055Z","title":"Makowsky","venue":null,"work_id":"71a5cd84-3b40-4955-8010-99ad2a428429","year":1987},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:03.853562Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:07240b21b4e840af82df3b46cdb7ed49e0c6c50e1dc2c52ce3003b86097260f2","observation_id":"b5cab50d-5026-46f5-8b95-1cd381d605c2","resolution":{"observed_at":"2026-08-06T20:04:11.725695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:11.289047Z","title":"Fine- grained evaluation of rule-and embedding-based systems for knowledge graph completion","venue":null,"work_id":"44f03410-6fe3-4a8c-9c47-f1c542af4bc7","year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.035695Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:1e1d08083513b229caea4740424f485eb60105b8ffcf7c84403319affd4566c9","observation_id":"5cc64427-aa13-47b1-8aa3-03bb024f27a8","resolution":{"observed_at":"2026-08-06T20:04:11.455308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:11.055962Z","title":"Anytime Bottom- Up Rule Learning for Knowledge Graph Completion, 2019","venue":null,"work_id":"e0ae291a-6d4c-4f1a-8c63-f8b10ea8c5bf","year":2019},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.198146Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:c31d5d4d1fdc5c7777fc9a7fd770ee0efe6990771c08a2e62ddace2bdb4e9ef9","observation_id":"38d1b3d1-cec2-4361-a6bc-3ccd0b920238","resolution":{"observed_at":"2026-08-06T20:04:11.177408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1301.3781","last_updated":"2013-09-07T00:30:40Z","snapshot_observed_at":"2026-07-06T03:04:11.148340Z","submitted_at":"2013-01-16T18:24:43Z","title":"Efficient Estimation of Word Representations in Vector Space","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1301.3781","snapshot_observed_at":"2026-08-06T20:04:04.330141Z","title":"Efficient estimation of word representations in vector space","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.330141Z"},"links":{"cited_paper":"/paper/1301.3781","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:9019333cc65a1b25ef23b193a1c4db9babe8fcb032e0585ac6457670a3601fb7","observation_id":"415b3d79-b1ef-4679-bd4d-19eb60b68815","resolution":{"observed_at":"2026-08-06T20:04:04.330141Z","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":"2026-08-06T20:04:10.840862Z","title":"Hierarchical graph embedding in vector space by graph pyramid","venue":null,"work_id":"c88ee183-943c-45ea-8499-6ec0587dfb8c","year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.407783Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:63ab1e56b961b931f09a4c769db833ff8f058bb5899a4aaae73a71dba80cbf9b","observation_id":"e86ac7dc-6c13-4d9b-8d79-de035b25fb9e","resolution":{"observed_at":"2026-08-06T20:04:10.881816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.01195","last_updated":"2019-06-04T04:59:08Z","snapshot_observed_at":"2026-07-06T07:57:43.002430Z","submitted_at":"2019-06-04T04:59:08Z","title":"Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs","version":1},"cited_work":{"arxiv_id":"1906.01195","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.01195","snapshot_observed_at":"2026-08-06T20:04:07.412676Z","title":"Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs","venue":"cs.LG","work_id":"28497eda-1d59-47fe-922b-2eb36832f19f","year":2019},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.536529Z"},"links":{"cited_paper":"/paper/1906.01195","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:702452e5fea7fcc1f212577c5cc92223c92312a2b49f5e7e6c7b626132e04858","observation_id":"fe9b575f-0651-4b47-aeff-1972c3591aa0","resolution":{"observed_at":"2026-08-06T20:04:07.501438Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.02121","last_updated":"2018-03-13T07:45:20Z","snapshot_observed_at":"2026-07-31T00:45:43.000232Z","submitted_at":"2017-12-06T10:41:47Z","title":"A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.02121","snapshot_observed_at":"2026-08-06T20:04:04.689818Z","title":"A novel embedding model for knowledge base completion based on convolutional neural network","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.689818Z"},"links":{"cited_paper":"/paper/1712.02121","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:892893b9deb3fdc3922402f303d78e7c758dfa6fbb37f9bb222dd0cc08cfa7d7","observation_id":"dbdc96d7-af55-44b7-81d2-6892a6c6e62b","resolution":{"observed_at":"2026-08-06T20:04:04.689818Z","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":"2026-08-06T20:04:10.549163Z","title":"Memory and Attention, 2020","venue":null,"work_id":"be3518cb-25e5-45ae-9d4b-6cccbb5f63e9","year":2020},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.812861Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:e624cd3053d45e29116c37b81a90f0b4415822feac3b5fc846257440c2d0f41a","observation_id":"6ee77f95-8f51-44ed-b40a-3dd8bcbb92aa","resolution":{"observed_at":"2026-08-06T20:04:10.691627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:10.294282Z","title":"Robust discovery of positive and negative rules in knowledge bases","venue":null,"work_id":"2e55f93d-643d-4d25-95bb-e836a4e930c5","year":2018},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:04.976677Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:bc9b6f3ba45d1ffdd9c937c91b29d597e8aa3a1de2020ec05022c33d79e6cd7e","observation_id":"a4916292-72c0-4a87-b4d6-3dd3c59f59b2","resolution":{"observed_at":"2026-08-06T20:04:10.392992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:10.001811Z","title":"Deepwalk: Online learning of social representations","venue":null,"work_id":"6d01696e-674c-4726-9b3d-ce810a905087","year":2014},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.130372Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:9adb679222957d6efecd6cb03c45eb650d1191c8cd985f10fd4aca2679478632","observation_id":"0327776d-5bd5-45f9-baab-7bd7f2cf6c23","resolution":{"observed_at":"2026-08-06T20:04:10.131009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.05909","last_updated":"2019-06-13T19:43:01Z","snapshot_observed_at":"2026-07-06T08:00:13.822686Z","submitted_at":"2019-06-13T19:43:01Z","title":"Stand-Alone Self-Attention in Vision Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.05909","snapshot_observed_at":"2026-08-06T20:04:05.259360Z","title":"Stand- alone self-attention in vision models","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.259360Z"},"links":{"cited_paper":"/paper/1906.05909","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:fc1251b04b868499995ce892418f26158877531f1a052af7f84acc137464fb87","observation_id":"b349a713-c645-4b6c-b308-132a8748da19","resolution":{"observed_at":"2026-08-06T20:04:05.259360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.00819","last_updated":"2021-01-21T21:15:36Z","snapshot_observed_at":"2026-08-02T11:31:40.163695Z","submitted_at":"2020-02-03T15:21:25Z","title":"Knowledge Graph Embedding for Link Prediction: A Comparative Analysis","version":4},"cited_work":{"arxiv_id":"2002.00819","doi":null,"metadata_source":"pith","pith_arxiv_id":"2002.00819","snapshot_observed_at":"2026-08-06T20:04:07.153943Z","title":"Knowledge Graph Embedding for Link Prediction: A Comparative Analysis","venue":"cs.LG","work_id":"3061674e-2ee2-4558-9599-22f8a6bbbf58","year":2020},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.419084Z"},"links":{"cited_paper":"/paper/2002.00819","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:2f3970aaa703e8a196306c4fb11dcbfbd7757be55a6e5b0354c9c24c100949e7","observation_id":"60211d37-1437-4d21-afda-1c3d7b3fc639","resolution":{"observed_at":"2026-08-06T20:04:07.260795Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:09.747301Z","title":"Dy- namic routing between capsules","venue":null,"work_id":"82d42245-d8c3-4dfd-98ae-b7ba65d91ec6","year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.546697Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:58480e403919481f785f376557ae3f73bf8bccd07e9978cf026371795ebe88f2","observation_id":"831a61d7-696e-4e5b-a092-f87b870fda8b","resolution":{"observed_at":"2026-08-06T20:04:09.854190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.08053","last_updated":"2020-03-13T23:45:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-09-17T19:42:54Z","title":"Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.08053","snapshot_observed_at":"2026-08-06T20:04:05.691716Z","title":"Megatron-lm: Training multi-billion parameter language models using gpu model parallelism","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.691716Z"},"links":{"cited_paper":"/paper/1909.08053","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:c05edd4920fd30af68d11862465a54fc7d3f7d556d353a4a9f748cb94a2f8a9f","observation_id":"38ca8a8d-a6e8-479e-b39f-cfe39bd371da","resolution":{"observed_at":"2026-08-06T20:04:05.691716Z","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":"2026-08-06T20:04:09.557802Z","title":"Line: Large-scale information network em- bedding","venue":null,"work_id":"e694f808-e04d-476e-a894-d7ba2c7acd91","year":2015},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.819809Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:2cb9beb8edef9466ffc371daf206a1ba7b217c5d939ecbae73daf7178dc89a86","observation_id":"1b507a47-4ce2-4b4f-9207-57e62ac4b49b","resolution":{"observed_at":"2026-08-06T20:04:09.636396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.10821","last_updated":"2020-05-21T17:55:59Z","snapshot_observed_at":"2026-08-07T22:28:45.550979Z","submitted_at":"2020-05-21T17:55:59Z","title":"Hierarchical Multi-Scale Attention for Semantic Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.10821","snapshot_observed_at":"2026-08-06T20:04:05.960210Z","title":"Hierarchi- cal multi-scale attention for semantic segmentation","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:05.960210Z"},"links":{"cited_paper":"/paper/2005.10821","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:8027b377515ede0bde6570f30ea8c033477821051fbcc70bee0c93a5b9aed362","observation_id":"2ca392af-555c-4e01-912f-8f975c124b4b","resolution":{"observed_at":"2026-08-06T20:04:05.960210Z","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":"2026-08-06T20:04:09.277873Z","title":"Observed versus latent features for knowledge base and text inference","venue":null,"work_id":"4ec500c8-bda4-4d70-8a6d-515aab937cea","year":2015},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.082726Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:7aa5e08c2687d2482e3bad277ec4d698d66dec6f2de12ed9668829e9b41c8c47","observation_id":"489fb351-5596-45e7-a5a3-4440b698ab0f","resolution":{"observed_at":"2026-08-06T20:04:09.425967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:09.044164Z","title":"Complex embeddings for simple link prediction","venue":null,"work_id":"2d843d0c-cacd-4ebd-9d1c-a3edbe1c484d","year":2016},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.203546Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:63cb919dbe60c311e07cea983b4f042588c5297b40018003d4874305e1f47539","observation_id":"6b534a44-8ef5-4c48-b1b2-9e8a99bd3921","resolution":{"observed_at":"2026-08-06T20:04:09.156414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1111.4503","last_updated":"2011-11-18T21:46:32Z","snapshot_observed_at":"2026-08-08T06:37:46.213719Z","submitted_at":"2011-11-18T21:46:32Z","title":"The Anatomy of the Facebook Social Graph","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1111.4503","snapshot_observed_at":"2026-08-06T20:04:06.344499Z","title":"The anatomy of the facebook social graph","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.344499Z"},"links":{"cited_paper":"/paper/1111.4503","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:521f3cf7510e9f0eac4ee006586baae573c80e5366c0da7a543e8fe2f8c53307","observation_id":"9813566c-3f9d-44e7-9906-6efdd372b05a","resolution":{"observed_at":"2026-08-06T20:04:06.344499Z","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":"2026-08-06T20:04:08.713180Z","title":"Attention is all you need","venue":null,"work_id":"47e9a2da-927e-4585-9faf-993ee26d6bb1","year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.457514Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:44c1a22466b35d5780f7c3ffed32f921f26b62e52e048045861ca8833a90de29","observation_id":"2c739930-c10c-491a-8c22-585216975a56","resolution":{"observed_at":"2026-08-06T20:04:08.884616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10903","last_updated":"2018-02-04T19:13:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-10-30T12:41:12Z","title":"Graph Attention Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10903","snapshot_observed_at":"2026-08-06T20:04:06.574563Z","title":"Graph attention networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.574563Z"},"links":{"cited_paper":"/paper/1710.10903","citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:5c0e652b99730e1f9379de34965dc4f9d3923917b3f10f2c2aa630019404c97e","observation_id":"3ae994fb-4ea4-4db8-8d63-30364fceda8b","resolution":{"observed_at":"2026-08-06T20:04:06.574563Z","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":"2026-08-06T20:04:08.488829Z","title":"A capsule network-based embedding model for knowl- edge graph completion and search personalization","venue":null,"work_id":"9767cfe3-ae95-47be-842c-d93b1c2fd343","year":2019},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.692595Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:237c6bec9cb69e452d748c82c6de2a0dd003769053b460217ac8052633cad2f3","observation_id":"6e76002d-445b-4d20-a32b-25ec6594d124","resolution":{"observed_at":"2026-08-06T20:04:08.618271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:08.255385Z","title":"Structural deep net- work embedding","venue":null,"work_id":"36ffc060-182b-4b2d-b371-b5e527c63fd1","year":2016},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.787983Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:9feb4133df8a4343021bf17f50d201fd20ee1d95e2f2500494265accc04af4b2","observation_id":"c4be68fe-abc6-432d-9902-8ab05d690c84","resolution":{"observed_at":"2026-08-06T20:04:08.367473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:04:08.048450Z","title":"Xlnet: Generalized autoregressive pretraining for language understanding","venue":null,"work_id":"595f98d2-7244-4d8e-ac36-71cf89f310de","year":2019},"citing_paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:06.929115Z"},"links":{"citing_paper":"/paper/2507.03947"},"observation_digest":"sha256:802539e71c6c22d3ed21004ca5cb55cc58a69dd3c4e9f3f190de2f466ee80701","observation_id":"a8fba5b7-620b-4eca-8860-d284239230d8","resolution":{"observed_at":"2026-08-06T20:04:08.098338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.03947","last_updated":"2025-07-30T12:47:25Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T19:56:43.081415Z","submitted_at":"2025-07-05T08:13:09Z","title":"Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":3,"verified_fuzzy":25},"total_outbound_references":44},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.03947."}