{"as_of":"2026-08-07T08:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b782f00632a98d0492493105e97547762a4d9dc2ff21d887670ffc95f0420c14","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:11:00.258328Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-24T06:29:00.687803Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":"2006.02516","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Anomaly detection with tensor networks","venue":null,"work_id":"5a3b40f6-483e-496f-bcac-43f665181c4d","year":2020},"citing_paper":{"arxiv_id":"2309.06577","last_updated":"2026-05-01T10:56:08Z","snapshot_observed_at":"2026-08-02T16:55:18.223163Z","submitted_at":"2023-09-11T08:05:09Z","title":"Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms","version":5},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-24T06:28:33.255228Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2309.06577"},"observation_digest":"sha256:0da3836bda713c495b03d415e7fb4aead52fe8b536e2539fbdace2c292a59e20","observation_id":"adb6792b-4c05-480f-8534-5de17464d94f","resolution":{"observed_at":"2026-05-24T06:29:00.692041Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":"2006.02516","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Anomaly detection with tensor networks","venue":null,"work_id":"5a3b40f6-483e-496f-bcac-43f665181c4d","year":2020},"citing_paper":{"arxiv_id":"2409.15030","last_updated":"2026-05-04T04:25:28Z","snapshot_observed_at":"2026-07-06T19:20:27.927724Z","submitted_at":"2024-09-23T13:55:58Z","title":"Anomaly Detection from a Tensor Train Perspective","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-23T20:42:43.521145Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2409.15030"},"observation_digest":"sha256:0ddfb1ed0abc8c2b2342b8e85f21f9efc1e658f7ed68a4ca215e763b109a7481","observation_id":"84c0d731-ac72-4b14-b8da-6bb096d7fda5","resolution":{"observed_at":"2026-05-23T20:43:25.187670Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-08-07T04:11:00.258328Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.11711","last_updated":"2025-06-13T12:27:34Z","snapshot_observed_at":"2026-08-07T04:01:51.505665Z","submitted_at":"2025-06-13T12:27:34Z","title":"Knapsack and Shortest Path Problems Generalizations From A Quantum-Inspired Tensor Network Perspective","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T04:11:00.258328Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2506.11711"},"observation_digest":"sha256:791aa82c3f37b086280b9e8c2c20a15f07327ec5c7a720c0032acb35c852b3ee","observation_id":"9e81c270-70cd-4b99-b06c-7d5d2831dd93","resolution":{"observed_at":"2026-08-07T04:11:00.258328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-08-03T08:32:01.275985Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2601.16734","last_updated":"2026-07-27T13:18:25Z","snapshot_observed_at":"2026-08-06T10:32:59.392178Z","submitted_at":"2026-01-23T13:31:16Z","title":"SeeMPS: A Python-based Matrix Product State and Tensor Train Library","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T08:32:01.275985Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2601.16734"},"observation_digest":"sha256:d3b5a2a9766888ab4a643440b9a6d2b2f98d45af6a9ce0f643cb5c2c45a9bbd6","observation_id":"bf888770-e308-4f73-9c92-ca4a12276412","resolution":{"observed_at":"2026-08-03T08:32:01.275985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":"2006.02516","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Anomaly detection with tensor networks","venue":null,"work_id":"5a3b40f6-483e-496f-bcac-43f665181c4d","year":2020},"citing_paper":{"arxiv_id":"2604.06265","last_updated":"2026-06-18T07:01:21Z","snapshot_observed_at":"2026-07-13T09:28:30.620949Z","submitted_at":"2026-04-07T02:37:45Z","title":"SMT-AD: a scalable quantum-inspired anomaly detection approach","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T19:51:34.023840Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2604.06265"},"observation_digest":"sha256:483dc4a3e8a67e0c4abef9782e101285ac1ae0c01c760d6f7403bb232fb8f4c0","observation_id":"764af9ae-7efe-4754-9c42-17dee61e564e","resolution":{"observed_at":"2026-05-10T22:25:52.829920Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":"2006.02516","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Anomaly detection with tensor networks","venue":null,"work_id":"5a3b40f6-483e-496f-bcac-43f665181c4d","year":2020},"citing_paper":{"arxiv_id":"2604.14287","last_updated":"2026-04-15T18:00:03Z","snapshot_observed_at":"2026-07-06T23:02:05.116649Z","submitted_at":"2026-04-15T18:00:03Z","title":"Quantum-inspired tensor networks in machine learning models","version":1},"reference_index":134,"source":"arxiv_source","source_observed_at":"2026-05-10T13:50:22.375333Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2604.14287"},"observation_digest":"sha256:866f93736baf780f02e7bf785ca109c3b7c9f9cc4f6321d6368625d5281295ba","observation_id":"cde0081f-d903-4cef-9d5b-bc4c6868789a","resolution":{"observed_at":"2026-05-10T14:10:29.109264Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks","version":2},"cited_work":{"arxiv_id":"2006.02516","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.02516","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Anomaly detection with tensor networks","venue":null,"work_id":"5a3b40f6-483e-496f-bcac-43f665181c4d","year":2020},"citing_paper":{"arxiv_id":"2605.17895","last_updated":"2026-05-18T06:00:48Z","snapshot_observed_at":"2026-07-06T23:28:50.117638Z","submitted_at":"2026-05-18T06:00:48Z","title":"Geometric Prototype Learning in Quantum Hilbert Space with Matrix Product States","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-20T11:43:54.791075Z"},"links":{"cited_paper":"/paper/2006.02516","citing_paper":"/paper/2605.17895"},"observation_digest":"sha256:288f04b148a03fc132b9d11183fa28750feff6f47b07f42ace421b4b95f09f89","observation_id":"f97c978c-4a15-4592-bd4a-5820d9310d15","resolution":{"observed_at":"2026-05-20T11:48:15.200672Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2006.02516/citation-record","integrity":"/paper/2006.02516/integrity","json":"/paper/2006.02516/citation-record.json","paper":"/paper/2006.02516"},"outbound":[],"paper":{"arxiv_id":"2006.02516","last_updated":"2020-06-16T18:03:37Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T06:22:05.973755Z","submitted_at":"2020-06-03T20:41:30Z","title":"Anomaly Detection with Tensor Networks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2006.02516."}