{"as_of":"2026-08-09T10:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f6fb2e82d3237c95137a0a22aacce6d87dd8262598e353b070fb3c38f4da6066","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T04:03:51.555264Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.22985/citation-record","integrity":"/paper/2607.22985/integrity","json":"/paper/2607.22985/citation-record.json","paper":"/paper/2607.22985"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.15825","last_updated":"2025-07-21T17:33:15Z","snapshot_observed_at":"2026-08-08T02:45:31.010752Z","submitted_at":"2025-07-21T17:33:15Z","title":"ACS: An interactive framework for conformal selection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.15825","snapshot_observed_at":"2026-08-01T04:03:50.821590Z","title":"ACS: An interactive framework for conformal selection.arXiv preprint arXiv:2507.15825,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.821590Z"},"links":{"cited_paper":"/paper/2507.15825","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:8728c784410f8620f64cbb9d9b09d6a1325fcd00c1e372ce4ae406d5621c71ce","observation_id":"2a3ba36c-742d-4b16-bb09-1ba6aa7a90d5","resolution":{"observed_at":"2026-08-01T04:03:50.821590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.03297","last_updated":"2026-07-18T07:42:03Z","snapshot_observed_at":"2026-08-07T03:48:04.342400Z","submitted_at":"2025-09-03T13:24:06Z","title":"Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.03297","snapshot_observed_at":"2026-08-01T04:03:50.945773Z","title":"Feedback- enhanced online multiple testing with applications to conformal selection.arXiv preprint arXiv:2509.03297,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.945773Z"},"links":{"cited_paper":"/paper/2509.03297","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:c8552686e2131d7facb13bfcf04c55d12a690128a9f27553494c240e8027f731","observation_id":"08124a11-beca-43bc-95b3-c9438b2486fb","resolution":{"observed_at":"2026-08-01T04:03:50.945773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:51.017923Z","title":"Yash Nair, Ying Jin, James Yang, and Emmanuel J Cand` es","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.017923Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:fa604f2ec07b382b0d53ccd415883dd4faeb03e729fc139e8e714c6d8d8915f3","observation_id":"86bf9467-873f-40da-8825-b0ad7ab7d850","resolution":{"observed_at":"2026-08-01T04:03:51.017923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:51.148179Z","title":"Published online","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.148179Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:e1d7a7b6729614422142de18431e38f17eb60c92b852dda5591b775804a33768","observation_id":"bcdf5938-44b9-46cc-a90d-151c7c549ae8","resolution":{"observed_at":"2026-08-01T04:03:51.148179Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:51.300037Z","title":"Cheap and fast–but is it good? Evaluating non-expert annotations for natural language tasks","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.300037Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:0709d5b09d93257ee14e86a3d53611a151dc88db44aa4456069b74844eb9b1d9","observation_id":"20423a06-3b10-43ff-9e71-f155e7529043","resolution":{"observed_at":"2026-08-01T04:03:51.300037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:50.752182Z","title":"Probably approximately correct labels.arXiv preprint arXiv:2506.10908,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":1995,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.752182Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:b47a81216012c444e11b299d572bad2c4c2525f58b23d7151d3c1b4d7dbbc5d5","observation_id":"c6cbebea-8c21-413b-95da-bde621d801e4","resolution":{"observed_at":"2026-08-01T04:03:50.752182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1406.2080","last_updated":"2015-04-10T16:44:00Z","snapshot_observed_at":"2026-07-06T03:45:47.981395Z","submitted_at":"2014-06-09T05:45:12Z","title":"Training Convolutional Networks with Noisy Labels","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1406.2080","snapshot_observed_at":"2026-08-01T04:03:51.362269Z","title":"Training convolutional networks with noisy labels.arXiv preprint arXiv:1406.2080,","venue":null,"work_id":null,"year":2080},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2008,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.362269Z"},"links":{"cited_paper":"/paper/1406.2080","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:3a48c80254e98f35ea3b5f912381df0531de95816907da43c2dc105d42dde5fa","observation_id":"3a52b9d9-6cc3-492d-93c2-f665c138c595","resolution":{"observed_at":"2026-08-01T04:03:51.362269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02514","last_updated":"2025-01-05T12:01:31Z","snapshot_observed_at":"2026-08-08T23:59:03.294320Z","submitted_at":"2025-01-05T12:01:31Z","title":"Selection from Hierarchical Data with Conformal e-values","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02514","snapshot_observed_at":"2026-08-01T04:03:50.881390Z","title":"Selection from hierarchical data with conformal e-values","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.881390Z"},"links":{"cited_paper":"/paper/2501.02514","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:9632d717da08c98d009cdfadee88f9dd196d31d94e843f4d34c683832ab1187f","observation_id":"8fb4a319-a8b4-471b-b3d1-793cd79eb4e2","resolution":{"observed_at":"2026-08-01T04:03:50.881390Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02648","last_updated":"2024-05-21T13:06:56Z","snapshot_observed_at":"2026-08-07T04:04:39.319970Z","submitted_at":"2024-05-04T12:22:02Z","title":"A Conformal Prediction Score that is Robust to Label Noise","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02648","snapshot_observed_at":"2026-08-01T04:03:51.088099Z","title":"A conformal prediction score that is robust to label noise.arXiv preprint arXiv:2405.02648,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.088099Z"},"links":{"cited_paper":"/paper/2405.02648","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:92e8788cc024369f97f8f1ecb81d2a7266e86b2b6a475b66a9a48a550359e1fa","observation_id":"01fc8ed1-20fb-47db-bdf9-121715f52396","resolution":{"observed_at":"2026-08-01T04:03:51.088099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:51.426318Z","title":"A unified framework for large-scale inference of classification: Error rate control and optimality.arXiv preprint arXiv:2504.07321,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.426318Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:a953fa2d20dad0ef63aef4ffaf44b0fbff56645420877ef496e63f649e25cb9c","observation_id":"4df8cef4-ff96-4d4b-a43f-5a13e3c7e284","resolution":{"observed_at":"2026-08-01T04:03:51.426318Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:51.555264Z","title":"A generalized e- value feature detection method with FDR control at multiple resolutions.arXiv preprint arXiv:2409.17039,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:51.555264Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:50fddec14ad1151ba019e4db76aea0b785d36d82297d3d63340abb414cf3dff0","observation_id":"638ee824-a617-4583-a5e1-41c8e460cfb6","resolution":{"observed_at":"2026-08-01T04:03:51.555264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11824","last_updated":"2026-03-06T03:35:34Z","snapshot_observed_at":"2026-07-06T19:52:07.342252Z","submitted_at":"2024-11-18T18:44:00Z","title":"Theoretical Foundations of Conformal Prediction","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11824","snapshot_observed_at":"2026-08-01T04:03:50.593169Z","title":"Theoretical founda- tions of conformal prediction.arXiv preprint arXiv:2411.11824,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.593169Z"},"links":{"cited_paper":"/paper/2411.11824","citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:eff994d44023c034aa39d59c43c75a7864522d9064aff98bef5ab667ba30072d","observation_id":"99c3bc6b-5c25-4c73-b8ab-023e04e133c2","resolution":{"observed_at":"2026-08-01T04:03:50.593169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:50.651765Z","title":"Conformal selective prediction with general risk control.arXiv preprint arXiv:2603.24704,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.651765Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:5e4e38e2c951d266be73d85237ad248fc29da2f7fc3edf41ab6c1a729a6fe67e","observation_id":"f7166247-2356-4070-9102-f7e09e35c630","resolution":{"observed_at":"2026-08-01T04:03:50.651765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:50.707510Z","title":"Controlling the false discovery rate via knockoffs.The Annals of Statistics, 43(5):2055–2085,","venue":null,"work_id":null,"year":2055},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.707510Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:a0da12ba206f95b995a8ec3be8c778ecea3e3f53f9103dd9a45fc6cfd0aa7856","observation_id":"559af364-0993-4915-9b88-d1b599ab34b5","resolution":{"observed_at":"2026-08-01T04:03:50.707510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T04:03:50.840402Z","title":"Davood Karimi, Haoran Dou, Simon K Warfield, and Ali Gholipour","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-01T04:03:50.840402Z"},"links":{"citing_paper":"/paper/2607.22985"},"observation_digest":"sha256:81d6968dfce30f6fa17ed8150ca3a65b02291da1a531bc4e38a90c8733ea1b90","observation_id":"fb3e26c2-6d1c-4931-8a2f-bf95bbfc5426","resolution":{"observed_at":"2026-08-01T04:03:50.840402Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.22985","last_updated":"2026-07-25T01:51:46Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-08T09:08:37.517158Z","submitted_at":"2026-07-25T01:51:46Z","title":"Robust Conformalized Selection with Noisy Responses"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":15},"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 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2607.22985."}