{"as_of":"2026-08-13T04:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4924d40c14156bcfd5e46cfa4db5f36e40a9971a62fc9045b24459e2bb4bcc1a","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:56:34.867849Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2411.15828/citation-record","integrity":"/paper/2411.15828/integrity","json":"/paper/2411.15828/citation-record.json","paper":"/paper/2411.15828"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:56:35.698979Z","title":"Abadi, P","venue":null,"work_id":"72afa72a-3252-4efc-9493-e5cf8bc34b91","year":2016},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.631687Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:dfda044d3c53769aa378efb87255dda776e4eee4afbc51be63288dac89eb5be2","observation_id":"c459c007-79ee-47f1-98fc-6dbb23024ea2","resolution":{"observed_at":"2026-08-12T13:56:35.705630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.676345Z","title":"Babu s ka and J","venue":null,"work_id":"a57ff924-351c-425c-8894-22483b46f27e","year":1991},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.638186Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:d0d39d80b89a43323714f9412124fa670012bd84630c7248c352fef781cf9dbd","observation_id":"064f1768-12f8-448a-8dd1-9cf5a995dd16","resolution":{"observed_at":"2026-08-12T13:56:35.682856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.654232Z","title":"Boffi, F","venue":null,"work_id":"e751d8eb-e21e-4023-a128-d79b5f341ffd","year":2013},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.644577Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:8690d13b89c4208ecf8289378aa9a96adebb480758e91f4e4ba3deb4807b5225","observation_id":"e81b0ee9-3cbe-4701-a270-859e3ea7cd26","resolution":{"observed_at":"2026-08-12T13:56:35.660710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.632548Z","title":null,"venue":null,"work_id":"9a490770-8cdb-4b42-9134-079b3e451e56","year":2007},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.654545Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:e5392780f60eb5cbe9dd024f3ca62c3542c44264244fe745f42fd171b3ce9bbe","observation_id":"5668438d-ab27-4cef-b43b-d09b5a6ab111","resolution":{"observed_at":"2026-08-12T13:56:35.639654Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.610828Z","title":"Costabel and M","venue":null,"work_id":"87e7ab42-d02d-4b5d-8737-9399919a9129","year":2003},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.670090Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:a827a4ea2b75ba124d2688e879ace668c76f3bb84da9ec62900f54b67f0b5aed","observation_id":"e2087db7-38d8-41a5-be6e-f52182046db7","resolution":{"observed_at":"2026-08-12T13:56:35.618229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.577846Z","title":null,"venue":null,"work_id":"e4c2f658-3b5d-4856-8e7c-5b3ef154dc0f","year":null},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.678687Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:c81794a2ff08ef174795ae27f46f851cd49b09111e6f8125b165b335bc9b9ab9","observation_id":"51afa893-c8d5-4981-a8bc-a6ccd13b5ca1","resolution":{"observed_at":"2026-08-12T13:56:35.593104Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.554256Z","title":"Du and H","venue":null,"work_id":"a166fd54-a984-4e67-ae6f-b9566184e18b","year":2020},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.694105Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:a3a03b4c1e6fba7f30dcac960f200d4a49aee8ac88ec568136a6c406c3ec06ff","observation_id":"19a03759-9d73-4ff0-8837-d412691984d1","resolution":{"observed_at":"2026-08-12T13:56:35.559174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.527709Z","title":null,"venue":null,"work_id":"9f165262-3947-43da-bbdf-cb4fc1fbf3db","year":2018},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.700227Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:6f476e8af8fb56397dd2a50b4af7dc384315a26235df9143f9b57d2eb776c57a","observation_id":"840d5fbd-e649-4c63-b949-359fbc69be89","resolution":{"observed_at":"2026-08-12T13:56:35.533582Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.499476Z","title":"Gastaldi","venue":null,"work_id":"14fa143e-0e6c-484f-8042-59cb545774d4","year":2023},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.709735Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:8ad0a73af55d9bd8c8e173f604084ee4227c5e89ab7c6c73ad0777c790a4514b","observation_id":"2712313e-6653-4e86-8b9c-da4aa4a1f7f8","resolution":{"observed_at":"2026-08-12T13:56:35.509493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.474758Z","title":null,"venue":null,"work_id":"e07c20b7-34bb-4311-979f-084d064aa31c","year":2020},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.717530Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:1be39814c2729ff9ab392aa49086716c73a86fed44e449e3a67f94079f0cc2e4","observation_id":"70e2d01c-30be-4329-9edd-b95ead7aedfe","resolution":{"observed_at":"2026-08-12T13:56:35.481587Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:34.723064Z","title":"Hiptmair","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.723064Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:8d2226d0fa7734a3b273716e6f9f325daecf358979a1f32b0a4ce4266386e77c","observation_id":"c2bf3fcd-93ad-4ea7-ba24-7b732bbd4a3d","resolution":{"observed_at":"2026-08-12T13:56:34.723064Z","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":"2026-08-12T13:56:35.438548Z","title":"Jiang and J","venue":null,"work_id":"410fca3b-f526-4348-89ec-1137837a44b9","year":2023},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.730864Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:2f059556ef534753a09ab02607abd17d2ff41885e6712c5d3e0cd5606bef6831","observation_id":"1f39ff7f-d861-49a8-9c5e-9840a5e799fa","resolution":{"observed_at":"2026-08-12T13:56:35.444447Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.421708Z","title":"Ciarlet Jr and G","venue":null,"work_id":"368ffc91-1669-4289-b197-356adae6ce53","year":2008},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.736444Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:0d7e9c6177e5f990d2932e967df9468a6360bcbb958cdeacaf3e3497aa271af9","observation_id":"ff594d03-548a-4944-a4a1-ca4b0c9c7db5","resolution":{"observed_at":"2026-08-12T13:56:35.426454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.400446Z","title":"Kwan and J","venue":null,"work_id":"05465157-db30-4192-b56f-ff67994537f6","year":2007},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.742036Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:2b9120ce9ba7990261eadd90d44362cc6833f7d3adf75e0f875c594b3a7f8340","observation_id":"7fbd4dc0-d452-4b02-86e2-a14297820b88","resolution":{"observed_at":"2026-08-12T13:56:35.408128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.380389Z","title":"Lagaris, A","venue":null,"work_id":"e37bc39a-4a04-46c4-853c-97168842f5e3","year":1997},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.748226Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:34bda074721e583ca8f3b409a7ec5dd33889273b8430848ba68feda388ef2372","observation_id":"3d04b4cc-fc97-42ab-b0e7-87a40e1f64f9","resolution":{"observed_at":"2026-08-12T13:56:35.388105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.352880Z","title":null,"venue":null,"work_id":"c8a855c4-35f0-4f7c-993a-1eb76d41faf9","year":2021},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.757342Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:13967d3865be59b4667c9e1d3059df48addc85935387480863991515784ade02","observation_id":"64ae209d-a207-44b6-9a83-7979a62a973a","resolution":{"observed_at":"2026-08-12T13:56:35.358322Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07805","last_updated":"2024-04-11T14:50:11Z","snapshot_observed_at":"2026-08-13T00:32:36.681766Z","submitted_at":"2024-04-11T14:50:11Z","title":"Tensor Neural Network Interpolation and Its Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07805","snapshot_observed_at":"2026-08-12T13:56:34.762297Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.762297Z"},"links":{"cited_paper":"/paper/2404.07805","citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:295496719dbaa66f68b75aeaeeb9bd5c9aa01a2c8eedcc7fb24eec10117eebf6","observation_id":"2c60dbd6-acd6-4613-97a8-91c45e21009a","resolution":{"observed_at":"2026-08-12T13:56:34.762297Z","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":"2026-08-12T13:56:35.331436Z","title":null,"venue":null,"work_id":"f0cf7bb6-5353-46d3-8480-8886202329a3","year":2017},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.770617Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:6cb3d3161fb819aabae55b77242e491b6dedd0c2a9715f7225fd8333b8480a03","observation_id":"0d0dced2-05bd-42bf-8c6e-11fe7ccfb354","resolution":{"observed_at":"2026-08-12T13:56:35.338399Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.308488Z","title":null,"venue":null,"work_id":"d38966d9-d696-425d-9a67-62614e07e447","year":2013},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.776905Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:8546070fdd6748f03ceb362b33615412831328f6f8a9c1d8d8d4c4e1ca56c647","observation_id":"4cb8b714-7582-42db-bb11-a8aa548a3f2d","resolution":{"observed_at":"2026-08-12T13:56:35.315219Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.273137Z","title":null,"venue":null,"work_id":"e33f18c6-2b79-4ea5-91dd-d1efd0e0ca16","year":2015},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.783292Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:aa146c4da0e69c396c5d4e8a67f49b376286bfedd6d7a2c5e90addf47128c4fe","observation_id":"20926ce2-008e-4c75-8ddd-201b69ea22c0","resolution":{"observed_at":"2026-08-12T13:56:35.286977Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.238868Z","title":null,"venue":null,"work_id":"41c24f5d-e92d-4ea4-9e2a-91129cb70056","year":2015},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.790047Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:eee0a94519bb9f78a46fa5a819353e00d75db415669ee2feec03e36717d26ae3","observation_id":"4de07a07-f30e-42f4-9c7d-c3a8f1d431ee","resolution":{"observed_at":"2026-08-12T13:56:35.252056Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.215205Z","title":null,"venue":null,"work_id":"c5cde595-3e06-49a1-b2ee-688765012a95","year":2003},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.796820Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:a15ee7c80c659cdcfbc0fa77da0bb40cc5b046af5fa99941b652b44404643f1b","observation_id":"bc34e69b-5267-4758-b9d6-f94042338971","resolution":{"observed_at":"2026-08-12T13:56:35.222795Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.184702Z","title":"Paszke, S","venue":null,"work_id":"931f5f75-75e6-4b18-aa32-3c08aa8fb589","year":2017},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.810927Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:96c3fdc6596641de8a588f781c66755222afad6ce07763595043072ca04a1f94","observation_id":"3341613f-9ffb-44c3-b0ee-158a04d7ebda","resolution":{"observed_at":"2026-08-12T13:56:35.192328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.155979Z","title":null,"venue":null,"work_id":"512b0c80-f9d8-4f82-85b4-d60e04ace37b","year":2011},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.824406Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:8c43df8311bb6b3137d1a865bdc7c92a0fedacc4cfad194b770710cf4ae742b0","observation_id":"c70bed1a-4f45-40a5-af9e-82c5b31614b2","resolution":{"observed_at":"2026-08-12T13:56:35.163986Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.125569Z","title":null,"venue":null,"work_id":"0c208842-3e47-45d9-b3a2-f4c89ce7cf38","year":2011},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.832738Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:802e263464443d289f4bb718d593e7fb6c474777e7fdb6e84b69dd6e4ad0d555","observation_id":"0c51623f-4f5d-404e-a2e9-f60ba3c67985","resolution":{"observed_at":"2026-08-12T13:56:35.133850Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.073025Z","title":"Sun and A","venue":null,"work_id":"fa90b712-48c4-441b-b514-33b7794c0361","year":2016},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.838531Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:deff90e495921b1d53d89d689ef2b2cfab76a701c78af97f674685ea784ee49a","observation_id":"75a58aba-6b66-4038-b696-e150a1ea1b27","resolution":{"observed_at":"2026-08-12T13:56:35.081545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.045450Z","title":null,"venue":null,"work_id":"b7377807-eb56-49b6-b776-2af5d25f3407","year":2024},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.844727Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:b87269424e2687391b138c981eaab62cd9878319e493ccbe11cab20a615b2c25","observation_id":"784b6807-b141-4e32-80b5-edb1acd29cd5","resolution":{"observed_at":"2026-08-12T13:56:35.052259Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:35.019697Z","title":null,"venue":null,"work_id":"e6d45a75-c953-4c94-a55d-2399bbe2f919","year":2024},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.852481Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:aa8a6cf2c0075c2555a6fc8e682281111a9a7b37b3e149027f3f3a08ec08a82a","observation_id":"c9530250-1cf3-47bd-b6f9-e4b0171caf30","resolution":{"observed_at":"2026-08-12T13:56:35.027436Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:34.993064Z","title":"Wang and H","venue":null,"work_id":"9dbee3d2-4072-4251-a63e-79ecdfe32c89","year":2024},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.860707Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:b99a43dca9a5d2cef995e8c5993fdf6460f92025ea5e2e8e8232aa52fe7f5242","observation_id":"e0ba83ef-55fb-4cbe-a5e5-8301348af804","resolution":{"observed_at":"2026-08-12T13:56:34.999887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:56:34.968452Z","title":null,"venue":null,"work_id":"cb11c334-94ed-42c1-a276-03478438d6ca","year":2027},"citing_paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-12T13:56:34.867849Z"},"links":{"citing_paper":"/paper/2411.15828"},"observation_digest":"sha256:d43f18236d3740826740be67a2a98ee4b61786b00f0d835b5f3bd77ca06e1bee","observation_id":"73a3e1a7-e2c3-475a-a99b-26151fcc0410","resolution":{"observed_at":"2026-08-12T13:56:34.977891Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.15828","last_updated":"2024-11-24T13:09:52Z","latest_version":1,"primary_category":"math.NA","snapshot_observed_at":"2026-08-12T13:49:26.963813Z","submitted_at":"2024-11-24T13:09:52Z","title":"FieldTNN-based machine learning method for Maxwell eigenvalue problems"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":30},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2411.15828."}