{"as_of":"2026-08-07T19:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6857ffffad9f3702a59fb93f9bce6bfd618b447014b112c354708ebfcf107673","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":"2026-08-07T06:34:17.273281+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":"2026-08-06T15:56:59.202089Z","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":"2026-05-16T07:23:00.093325Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2207.10081","last_updated":"2022-07-20T04:44:26Z","snapshot_observed_at":"2026-07-06T13:33:32.029850Z","submitted_at":"2022-07-20T04:44:26Z","title":"What Do We Maximize in Self-Supervised Learning?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.10081","snapshot_observed_at":"2026-08-06T15:56:59.202089Z","title":"What Do We Maximize in Self-Supervised Learning?, July 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.14748","last_updated":"2025-07-19T20:48:46Z","snapshot_observed_at":"2026-08-07T00:04:27.004989Z","submitted_at":"2025-07-19T20:48:46Z","title":"Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T15:56:59.202089Z"},"links":{"cited_paper":"/paper/2207.10081","citing_paper":"/paper/2507.14748"},"observation_digest":"sha256:b36de05c3f09bf4a93dfbcfafce2019afb3d85af3c11b7096a91a62f75bab736","observation_id":"b9fa943e-ddb7-497a-812a-13bf5d882391","resolution":{"observed_at":"2026-08-06T15:56:59.202089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.10081","last_updated":"2022-07-20T04:44:26Z","snapshot_observed_at":"2026-07-06T13:33:32.029850Z","submitted_at":"2022-07-20T04:44:26Z","title":"What Do We Maximize in Self-Supervised Learning?","version":1},"cited_work":{"arxiv_id":"2207.10081","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2207.10081","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2207.10081 , year=","venue":null,"work_id":"a9e8e358-937b-4863-ae84-57f632511a16","year":null},"citing_paper":{"arxiv_id":"2511.08544","last_updated":"2025-11-14T08:38:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-11T18:21:55Z","title":"LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics","version":3},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-16T07:22:59.854042Z"},"links":{"cited_paper":"/paper/2207.10081","citing_paper":"/paper/2511.08544"},"observation_digest":"sha256:6b8523ff72c5f62d3dc1c90903eff63d2fd800e30036d76c98aa44d88445c72f","observation_id":"5094a2bc-0d6a-4158-adc0-3b6c84548893","resolution":{"observed_at":"2026-05-16T07:23:00.095241Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2207.10081/citation-record","integrity":"/paper/2207.10081/integrity","json":"/paper/2207.10081/citation-record.json","paper":"/paper/2207.10081"},"outbound":[],"paper":{"arxiv_id":"2207.10081","last_updated":"2022-07-20T04:44:26Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T13:33:32.029850Z","submitted_at":"2022-07-20T04:44:26Z","title":"What Do We Maximize in Self-Supervised Learning?"},"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 2 inbound Pith citation observations for arXiv:2207.10081."}