{"as_of":"2026-08-14T21:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2bf921db68dfb1c5fcc2e23bbf8ea6786a541443f4fd039ce770495149df7778","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T00:04:50.597035Z","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":"2026-07-03T16:08:37.733321Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-08-12T00:04:50.597035Z","title":", Newey, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02105","last_updated":"2025-12-10T22:43:54Z","snapshot_observed_at":"2026-08-14T02:50:32.491797Z","submitted_at":"2024-12-03T02:57:33Z","title":"The causal effects of modified treatment policies under network interference","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T00:04:50.597035Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2412.02105"},"observation_digest":"sha256:b2a6fc7c22dc27a92e9504a3257c733c746942e84ecff03360893d99c75ef741","observation_id":"ef1cf878-9906-4e17-b0fe-f8e7379de56d","resolution":{"observed_at":"2026-08-12T00:04:50.597035Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-08-10T21:29:07.801153Z","title":"Newey, Victor Quintas-Martinez, and Vasilis Syrgka- nis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.04871","last_updated":"2025-02-04T22:04:32Z","snapshot_observed_at":"2026-08-12T17:09:55.473781Z","submitted_at":"2025-01-08T23:04:32Z","title":"RieszBoost: Gradient Boosting for Riesz Regression","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.801153Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:36022122c07d068803a4b28f7b6c9859627a72c535d177878af6f6bbcc7fa4ba","observation_id":"6bebe191-8c0d-448b-83e7-9cf18f3f557f","resolution":{"observed_at":"2026-08-10T21:29:07.801153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-08-07T00:15:58.134775Z","title":"Chernozhukov, W","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14950","last_updated":"2025-06-23T18:27:16Z","snapshot_observed_at":"2026-08-12T15:53:15.901853Z","submitted_at":"2025-06-17T20:00:34Z","title":"Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T00:15:58.134775Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2506.14950"},"observation_digest":"sha256:0769fa6e1549e6d20cb07473179def08b8e53e2d0d01876db95535d510e184fe","observation_id":"467eeaf7-ac52-4087-899f-98818b29b959","resolution":{"observed_at":"2026-08-07T00:15:58.134775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-08-05T05:11:00.679014Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.05852","last_updated":"2025-09-06T22:29:17Z","snapshot_observed_at":"2026-08-12T23:11:56.614995Z","submitted_at":"2025-09-06T22:29:17Z","title":"Fisher Random Walk: Automatic Debiasing Contextual Preference Inference for Large Language Model Evaluation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T05:11:00.679014Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2509.05852"},"observation_digest":"sha256:8b10da4c52dc3164a4994b03704f8e209657e5d112f5ca595f545186b5a58f7d","observation_id":"813aaf2d-780f-4d19-88bf-0b8e1988c963","resolution":{"observed_at":"2026-08-05T05:11:00.679014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":"2104.14737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-07-03T16:08:37.733321Z","title":"arXiv preprint arXiv:2104.14737 , year=","venue":null,"work_id":"fc8e4fc6-9f67-4443-9f27-411fa3caeb48","year":2021},"citing_paper":{"arxiv_id":"2511.08303","last_updated":"2026-05-03T14:46:54Z","snapshot_observed_at":"2026-07-06T22:35:31.750339Z","submitted_at":"2025-11-11T14:35:18Z","title":"Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-17T23:47:56.278028Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2511.08303"},"observation_digest":"sha256:ce5d3eb7ddac7dd2502608b407feb3e1e08943dd271d3f08ac3b5648f54041bb","observation_id":"df01980d-41fb-427a-b7e1-2439db413f21","resolution":{"observed_at":"2026-05-17T23:50:31.401713Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":"2104.14737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-07-03T16:08:37.733321Z","title":"arXiv preprint arXiv:2104.14737 , year=","venue":null,"work_id":"fc8e4fc6-9f67-4443-9f27-411fa3caeb48","year":2021},"citing_paper":{"arxiv_id":"2604.19296","last_updated":"2026-04-21T10:02:36Z","snapshot_observed_at":"2026-07-06T23:05:58.167533Z","submitted_at":"2026-04-21T10:02:36Z","title":"Debiased neural operators for estimating functionals","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T02:34:43.887877Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2604.19296"},"observation_digest":"sha256:c652d3a9a7c0a79b584276267a17dc7185682ad2cf3f490cc9c79b65f18f5d12","observation_id":"0e3c9e23-1452-412b-8f86-cce8a0969116","resolution":{"observed_at":"2026-05-11T12:56:10.608280Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":"2104.14737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-07-03T16:08:37.733321Z","title":"arXiv preprint arXiv:2104.14737 , year=","venue":null,"work_id":"fc8e4fc6-9f67-4443-9f27-411fa3caeb48","year":2021},"citing_paper":{"arxiv_id":"2605.06386","last_updated":"2026-05-07T15:02:47Z","snapshot_observed_at":"2026-08-02T07:57:34.158260Z","submitted_at":"2026-05-07T15:02:47Z","title":"Covariate Balancing and Riesz Regression Should Be Guided by the Neyman Orthogonal Score in Debiased Machine Learning","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-08T03:40:31.516951Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2605.06386"},"observation_digest":"sha256:36a012ae6976fd5a701eb38738ee4dcda6c869712a9b36c88299c24733be3c8f","observation_id":"b90eb5c5-3023-4c25-a1f7-75784a056bd1","resolution":{"observed_at":"2026-05-11T21:56:36.687904Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":"2104.14737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-07-03T16:08:37.733321Z","title":"arXiv preprint arXiv:2104.14737 , year=","venue":null,"work_id":"fc8e4fc6-9f67-4443-9f27-411fa3caeb48","year":2021},"citing_paper":{"arxiv_id":"2605.17910","last_updated":"2026-05-18T06:16:18Z","snapshot_observed_at":"2026-08-01T21:35:10.288831Z","submitted_at":"2026-05-18T06:16:18Z","title":"Double/Debiased Machine Learning for Continuous Treatment Effects in Panel Data with Endogeneity","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-05-20T01:33:29.310455Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2605.17910"},"observation_digest":"sha256:5d6673e07ca6e230c06828a96fdcf80f4cf48af86dfb7e5029d26fe84312ecba","observation_id":"811a867c-141f-44bd-bb1c-442c8b03a3aa","resolution":{"observed_at":"2026-05-20T01:37:55.989829Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":"2104.14737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-07-03T16:08:37.733321Z","title":"arXiv preprint arXiv:2104.14737 , year=","venue":null,"work_id":"fc8e4fc6-9f67-4443-9f27-411fa3caeb48","year":2021},"citing_paper":{"arxiv_id":"2606.12892","last_updated":"2026-06-11T04:37:03Z","snapshot_observed_at":"2026-08-07T08:41:56.182463Z","submitted_at":"2026-06-11T04:37:03Z","title":"Prediction-Powered Causal Inference by Automatic Debiased Machine Learning and Semi-Supervised Riesz Regression","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-06-27T06:03:27.037381Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2606.12892"},"observation_digest":"sha256:d8a005b6e53cfb74b40c4f2388c32ff328083d48c6700472cf65a82cfe4eff77","observation_id":"d16d3d40-cbb1-43ea-a04f-52afb544efff","resolution":{"observed_at":"2026-07-03T16:08:37.734744Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.14737","snapshot_observed_at":"2026-08-01T03:25:08.923182Z","title":"K., Quintas-Martinez, V","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27685","last_updated":"2026-07-30T05:05:25Z","snapshot_observed_at":"2026-08-13T16:11:24.404746Z","submitted_at":"2026-07-30T05:05:25Z","title":"On regression with estimated covariates and conditional effects given the propensity score","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T03:25:08.923182Z"},"links":{"cited_paper":"/paper/2104.14737","citing_paper":"/paper/2607.27685"},"observation_digest":"sha256:f313fd9ded0be886391e164035fc4f76ea133f6aba6dc332184b9be49120c1a3","observation_id":"6f16b1cf-34b5-4cd2-a8f6-3a3bc07e69b0","resolution":{"observed_at":"2026-08-01T03:25:08.923182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2104.14737/citation-record","integrity":"/paper/2104.14737/integrity","json":"/paper/2104.14737/citation-record.json","paper":"/paper/2104.14737"},"outbound":[],"paper":{"arxiv_id":"2104.14737","last_updated":"2024-03-14T20:38:25Z","latest_version":3,"primary_category":"math.ST","snapshot_observed_at":"2026-08-09T04:16:29.345426Z","submitted_at":"2021-04-30T03:18:54Z","title":"Automatic Debiased Machine Learning via Riesz Regression"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2104.14737."}