{"as_of":"2026-08-23T17:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:efde4eda6639189eca0cafc96c48ad6fd09e9697e93c304541a4a375f21a03aa","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:17:17.478134Z","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":"2026-05-11T23:36:39.786702Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.07162","last_updated":"2020-02-15T00:10:35Z","snapshot_observed_at":"2026-08-07T21:40:26.559125Z","submitted_at":"2019-10-16T04:12:50Z","title":"Conditional Learning of Fair Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.07162","snapshot_observed_at":"2026-08-12T18:17:17.478134Z","title":"Conditional learning of fair representations","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2411.11939","last_updated":"2024-11-18T16:50:34Z","snapshot_observed_at":"2026-08-16T18:00:29.511590Z","submitted_at":"2024-11-18T16:50:34Z","title":"Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-12T18:17:17.478134Z"},"links":{"cited_paper":"/paper/1910.07162","citing_paper":"/paper/2411.11939"},"observation_digest":"sha256:166008ad1d1b7323b88352c2934ecf9ffb7aae386ff63b5332db4ca733131ca4","observation_id":"1f3466d2-0527-4494-84ff-204aa12d4d59","resolution":{"observed_at":"2026-08-12T18:17:17.478134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.07162","last_updated":"2020-02-15T00:10:35Z","snapshot_observed_at":"2026-08-07T21:40:26.559125Z","submitted_at":"2019-10-16T04:12:50Z","title":"Conditional Learning of Fair Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.07162","snapshot_observed_at":"2026-08-11T10:33:20.153207Z","title":"Conditional learning of fair representations,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2412.16542","last_updated":"2024-12-21T08:57:00Z","snapshot_observed_at":"2026-08-15T18:50:05.611839Z","submitted_at":"2024-12-21T08:57:00Z","title":"FairDD: Enhancing Fairness with domain-incremental learning in dermatological disease diagnosis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T10:33:20.153207Z"},"links":{"cited_paper":"/paper/1910.07162","citing_paper":"/paper/2412.16542"},"observation_digest":"sha256:9705a477628b5c0cc07cb73b3f35e1b48826fb02932cc91f501f274fcc30edb0","observation_id":"71a90240-897a-4788-8d3a-2ee3706cbda9","resolution":{"observed_at":"2026-08-11T10:33:20.153207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.07162","last_updated":"2020-02-15T00:10:35Z","snapshot_observed_at":"2026-08-07T21:40:26.559125Z","submitted_at":"2019-10-16T04:12:50Z","title":"Conditional Learning of Fair Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.07162","snapshot_observed_at":"2026-08-07T14:51:28.557536Z","title":"Conditional learning of fair representations","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.17533","last_updated":"2025-05-23T06:40:24Z","snapshot_observed_at":"2026-08-07T14:43:03.241943Z","submitted_at":"2025-05-23T06:40:24Z","title":"Learning Representational Disparities","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:51:28.557536Z"},"links":{"cited_paper":"/paper/1910.07162","citing_paper":"/paper/2505.17533"},"observation_digest":"sha256:a2b3dee3e493700602da15be304d2ed2b8bc07f0bbe52e8bfa4857d7abed079f","observation_id":"fa30fddd-d5a8-4d9d-a617-ad3811966a49","resolution":{"observed_at":"2026-08-07T14:51:28.557536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.07162","last_updated":"2020-02-15T00:10:35Z","snapshot_observed_at":"2026-08-07T21:40:26.559125Z","submitted_at":"2019-10-16T04:12:50Z","title":"Conditional Learning of Fair Representations","version":3},"cited_work":{"arxiv_id":"1910.07162","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.07162","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"72fd976b-5372-40a4-990f-f0c9ec6a212c","year":1910},"citing_paper":{"arxiv_id":"2604.26991","last_updated":"2026-06-09T11:11:43Z","snapshot_observed_at":"2026-08-02T01:07:20.319555Z","submitted_at":"2026-04-28T22:13:36Z","title":"People-Centred Medical Image Analysis via Fairness-Aware Human-AI Cooperation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-07T16:35:26.022291Z"},"links":{"cited_paper":"/paper/1910.07162","citing_paper":"/paper/2604.26991"},"observation_digest":"sha256:d42997b98784090168deb2874c2429e9f0315439b250e7209f7fa957305a30ca","observation_id":"26b6c300-4728-4f06-bfd5-fbf7c4fb1c94","resolution":{"observed_at":"2026-05-11T23:36:39.792812Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1910.07162/citation-record","integrity":"/paper/1910.07162/integrity","json":"/paper/1910.07162/citation-record.json","paper":"/paper/1910.07162"},"outbound":[],"paper":{"arxiv_id":"1910.07162","last_updated":"2020-02-15T00:10:35Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T21:40:26.559125Z","submitted_at":"2019-10-16T04:12:50Z","title":"Conditional Learning of Fair Representations"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.07162."}