{"as_of":"2026-08-08T19:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec479edd47b7649658b9de50043da5e915218b412b8b3df5dfdab649e9c17315","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:03:45.843358Z","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":"2026-05-23T02:25:19.666416Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":"2202.05433","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A survey on programmatic weak supervision.arXiv preprint arXiv:2202.05433","venue":null,"work_id":"83e8a10b-cf12-44c6-98c3-90e1621eb0ef","year":2022},"citing_paper":{"arxiv_id":"2502.18036","last_updated":"2026-04-22T02:19:48Z","snapshot_observed_at":"2026-08-02T22:41:05.099083Z","submitted_at":"2025-02-25T09:48:53Z","title":"Harnessing Multiple Large Language Models: A Survey on LLM Ensemble","version":6},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-23T02:22:28.649071Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2502.18036"},"observation_digest":"sha256:f3d1dbc4d8bd5a6c62dc4d6d90820f2a23e23505797779b7cad8fe945adf5304","observation_id":"6e42ec6d-4d2d-4fad-8645-e9c5e6b2c813","resolution":{"observed_at":"2026-05-23T02:25:19.668521Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-07T12:50:35.903602Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23470","last_updated":"2025-06-04T04:14:44Z","snapshot_observed_at":"2026-08-07T21:40:10.262019Z","submitted_at":"2025-05-29T14:26:11Z","title":"Refining Labeling Functions with Limited Labeled Data","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:50:35.903602Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2505.23470"},"observation_digest":"sha256:053643464642d9b234b4855bc84873cb44736af0dfddaef0c3e9b6bfdc79e4f9","observation_id":"786d2e69-08f7-4803-a8d8-e065e40912eb","resolution":{"observed_at":"2026-08-07T12:50:35.903602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-07T11:26:47.432114Z","title":"A survey on programmatic weak supervision","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.02451","last_updated":"2025-06-03T05:16:18Z","snapshot_observed_at":"2026-08-08T15:08:22.530546Z","submitted_at":"2025-06-03T05:16:18Z","title":"Weak Supervision for Real World Graphs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:47.432114Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2506.02451"},"observation_digest":"sha256:67623723a6e0a841a33241ff3df5e5ae35e738832be68cafdde5c6f594ba34e0","observation_id":"2e8b8e2d-43f4-4bcc-b6c1-510c5ac2ddbd","resolution":{"observed_at":"2026-08-07T11:26:47.432114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-07T04:40:25.737399Z","title":"A survey on programmatic weak supervision.arXiv preprint arXiv:2202.05433,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.10259","last_updated":"2025-06-12T00:58:37Z","snapshot_observed_at":"2026-08-08T05:12:26.830473Z","submitted_at":"2025-06-12T00:58:37Z","title":"Meta-learning Representations for Learning from Multiple Annotators","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-07T04:40:25.737399Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2506.10259"},"observation_digest":"sha256:84cdfb25276f0c20f797913eba23e4ce4ade2c7c7e0475db9db2ccdd414e8498","observation_id":"41b904eb-310f-4635-a96f-be0397848f14","resolution":{"observed_at":"2026-08-07T04:40:25.737399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-07T15:03:45.843358Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.18770","last_updated":"2025-05-22T09:36:17Z","snapshot_observed_at":"2026-08-08T07:36:05.506463Z","submitted_at":"2025-05-22T09:36:17Z","title":"Importance of User Control in Data-Centric Steering for Healthcare Experts","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T15:03:45.843358Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2506.18770"},"observation_digest":"sha256:09fbdfca308e316a21c801d64836ec382ef70a7f1f0c4e05695f3ce9119f8599","observation_id":"922ea992-5839-4689-b6f9-61ebfb670af1","resolution":{"observed_at":"2026-08-07T15:03:45.843358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-06T18:47:53.603967Z","title":"& Ratner, A","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.07421","last_updated":"2025-07-10T04:31:01Z","snapshot_observed_at":"2026-08-08T07:57:00.707301Z","submitted_at":"2025-07-10T04:31:01Z","title":"SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T18:47:53.603967Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2507.07421"},"observation_digest":"sha256:f5ae4ca8108ab6117799cdcf865a6de10a8ac07dab75b0807a09ed45d675a859","observation_id":"71be5a8e-c3db-4331-bd93-a70355b58c0a","resolution":{"observed_at":"2026-08-06T18:47:53.603967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-08-06T17:03:34.278926Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12004","last_updated":"2025-07-16T07:58:20Z","snapshot_observed_at":"2026-08-07T12:43:44.020373Z","submitted_at":"2025-07-16T07:58:20Z","title":"Improving Data and Parameter Efficiency of Neural Language Models Using Representation Analysis","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T17:03:34.278926Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2507.12004"},"observation_digest":"sha256:b2f51c7e61503e3b737a85a2ceec87c88b9b3049dc799af6daaf3a83d8b4aefd","observation_id":"8895219a-0088-4aa9-bb5b-69cb83900c4d","resolution":{"observed_at":"2026-08-06T17:03:34.278926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision","version":2},"cited_work":{"arxiv_id":"2202.05433","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2202.05433","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A survey on programmatic weak supervision.arXiv preprint arXiv:2202.05433","venue":null,"work_id":"83e8a10b-cf12-44c6-98c3-90e1621eb0ef","year":2022},"citing_paper":{"arxiv_id":"2605.01874","last_updated":"2026-05-03T13:37:17Z","snapshot_observed_at":"2026-08-04T00:41:40.512499Z","submitted_at":"2026-05-03T13:37:17Z","title":"Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-10T16:24:38.758066Z"},"links":{"cited_paper":"/paper/2202.05433","citing_paper":"/paper/2605.01874"},"observation_digest":"sha256:ca9be8386a222c38a405b645740daf8358db721b02faca08bd3d25ac729197ed","observation_id":"a3a8498e-1130-4a28-a3b1-ed6e565b749b","resolution":{"observed_at":"2026-05-11T08:56:01.636712Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2202.05433/citation-record","integrity":"/paper/2202.05433/integrity","json":"/paper/2202.05433/citation-record.json","paper":"/paper/2202.05433"},"outbound":[],"paper":{"arxiv_id":"2202.05433","last_updated":"2022-02-14T05:45:58Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T12:36:41.820948Z","submitted_at":"2022-02-11T04:05:38Z","title":"A Survey on Programmatic Weak Supervision"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2202.05433."}