{"as_of":"2026-08-16T14:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c6b55536e62593b0b8c1f746c03a4b0cd5d3ece1ce2194a6adbd9dc9b6f9f5a8","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T00:41:47.839826Z","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":"2026-07-04T08:19:44.372614Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2010.10090","last_updated":"2020-10-20T07:33:21Z","snapshot_observed_at":"2026-08-16T07:14:12.935585Z","submitted_at":"2020-10-20T07:33:21Z","title":"Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher","version":1},"cited_work":{"arxiv_id":"2010.10090","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.10090","snapshot_observed_at":"2026-07-04T08:19:44.372614Z","title":"Knowledge distillation in wide neural networks: Risk bound, data efficiency and imperfect teacher","venue":null,"work_id":"a8fa9d58-52fa-4348-a1b5-5923c1999268","year":2020},"citing_paper":{"arxiv_id":"2605.13143","last_updated":"2026-05-15T03:25:35Z","snapshot_observed_at":"2026-08-13T18:50:34.604945Z","submitted_at":"2026-05-13T08:10:05Z","title":"On the Generalization of Knowledge Distillation: An Information-Theoretic View","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-19T18:03:07.434428Z"},"links":{"cited_paper":"/paper/2010.10090","citing_paper":"/paper/2605.13143"},"observation_digest":"sha256:d2de45e0cc05780132542ffb4d1babfa8359500e4f918a15348e7fd80fee4c51","observation_id":"a94b7d40-de6f-4dc4-9aa1-dc4d7a99549c","resolution":{"observed_at":"2026-05-19T18:03:10.039803Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.10090","last_updated":"2020-10-20T07:33:21Z","snapshot_observed_at":"2026-08-16T07:14:12.935585Z","submitted_at":"2020-10-20T07:33:21Z","title":"Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher","version":1},"cited_work":{"arxiv_id":"2010.10090","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.10090","snapshot_observed_at":"2026-07-04T08:19:44.372614Z","title":"Knowledge distillation in wide neural networks: Risk bound, data efficiency and imperfect teacher","venue":null,"work_id":"a8fa9d58-52fa-4348-a1b5-5923c1999268","year":2020},"citing_paper":{"arxiv_id":"2606.22019","last_updated":"2026-06-20T12:48:31Z","snapshot_observed_at":"2026-08-06T19:21:18.734073Z","submitted_at":"2026-06-20T12:48:31Z","title":"Channel Location Constrains the Auditability of Subliminal Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-26T11:52:03.948568Z"},"links":{"cited_paper":"/paper/2010.10090","citing_paper":"/paper/2606.22019"},"observation_digest":"sha256:8c565849d815ecec25777cd517bf767716ff0e04e619706c2430a44fb6b1ce0c","observation_id":"f20bce9f-ff68-4920-92f5-bab53b5824aa","resolution":{"observed_at":"2026-07-04T08:19:44.374065Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.10090","last_updated":"2020-10-20T07:33:21Z","snapshot_observed_at":"2026-08-16T07:14:12.935585Z","submitted_at":"2020-10-20T07:33:21Z","title":"Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.10090","snapshot_observed_at":"2026-08-02T00:41:47.839826Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.14947","last_updated":"2026-07-16T12:57:00Z","snapshot_observed_at":"2026-08-09T11:25:01.860063Z","submitted_at":"2026-07-16T12:57:00Z","title":"Optimal Self-Distillation for Rectified Flow via Linear Probing","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-02T00:41:47.839826Z"},"links":{"cited_paper":"/paper/2010.10090","citing_paper":"/paper/2607.14947"},"observation_digest":"sha256:2c8932d35909881e27f2587a8f87af399b8fa2457aa69cbbbd1ef87d563ec0d3","observation_id":"471187d8-1150-47f1-be0f-e4c1fe22a198","resolution":{"observed_at":"2026-08-02T00:41:47.839826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2010.10090/citation-record","integrity":"/paper/2010.10090/integrity","json":"/paper/2010.10090/citation-record.json","paper":"/paper/2010.10090"},"outbound":[],"paper":{"arxiv_id":"2010.10090","last_updated":"2020-10-20T07:33:21Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T07:14:12.935585Z","submitted_at":"2020-10-20T07:33:21Z","title":"Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.10090."}