{"as_of":"2026-08-09T07:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4bf534b8f2aa4053c926a7395fcebbe6595ca3b7aead4ff3bc748cf34921d479","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:19:21.047681Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T22:31:45.861659Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2012.10931","last_updated":"2021-03-11T09:16:45Z","snapshot_observed_at":"2026-07-06T10:26:16.221193Z","submitted_at":"2020-12-20T14:16:41Z","title":"Recent advances in deep learning theory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.10931","snapshot_observed_at":"2026-08-07T15:19:21.047681Z","title":"Recent advances in deep learning theory","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.15628","last_updated":"2025-05-21T15:14:34Z","snapshot_observed_at":"2026-08-08T02:16:21.927195Z","submitted_at":"2025-05-21T15:14:34Z","title":"SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision Tasks","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:19:21.047681Z"},"links":{"cited_paper":"/paper/2012.10931","citing_paper":"/paper/2505.15628"},"observation_digest":"sha256:b10202bfe3c3a8d6e5aa31e5d450b2ac47203892266ba4311c6fa3aa0306b0c2","observation_id":"6cf7d35d-0f35-4928-b9b8-ce52546ffdb5","resolution":{"observed_at":"2026-08-07T15:19:21.047681Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.10931","last_updated":"2021-03-11T09:16:45Z","snapshot_observed_at":"2026-07-06T10:26:16.221193Z","submitted_at":"2020-12-20T14:16:41Z","title":"Recent advances in deep learning theory","version":2},"cited_work":{"arxiv_id":"2012.10931","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.10931","snapshot_observed_at":"2026-08-06T22:31:45.861659Z","title":"Recent advances in deep learning theory","venue":"cs.LG","work_id":"d6e263cc-1f5b-4ab0-a7ee-17f55e02fb9b","year":2020},"citing_paper":{"arxiv_id":"2506.21484","last_updated":"2025-06-26T17:12:58Z","snapshot_observed_at":"2026-08-08T23:52:37.745609Z","submitted_at":"2025-06-26T17:12:58Z","title":"TITAN: Query-Token based Domain Adaptive Adversarial Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T22:31:37.620908Z"},"links":{"cited_paper":"/paper/2012.10931","citing_paper":"/paper/2506.21484"},"observation_digest":"sha256:1ad476adf48d57b4d6b4b0c1c43359553e5fb963d1a330ece0c2768a23b1bdb4","observation_id":"28c6aa98-d003-48a0-96eb-449dab73a36d","resolution":{"observed_at":"2026-08-06T22:31:45.957489Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2012.10931/citation-record","integrity":"/paper/2012.10931/integrity","json":"/paper/2012.10931/citation-record.json","paper":"/paper/2012.10931"},"outbound":[],"paper":{"arxiv_id":"2012.10931","last_updated":"2021-03-11T09:16:45Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T10:26:16.221193Z","submitted_at":"2020-12-20T14:16:41Z","title":"Recent advances in deep learning theory"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2012.10931."}