{"as_of":"2026-08-16T06:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c944c3e248ad5eb5741830211f41542453c36d39f5a1faee323fceb0352029a8","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:29:07.899920Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T03:05:44.393410Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_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},"cited_work":{"arxiv_id":"2501.04871","doi":"10.48550/arxiv.2501.04871","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.04871","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Lee and Alejandro Schuler","venue":"arXiv (Cornell University)","work_id":"d22a53d9-1bab-455d-a044-90866d5b36ee","year":2025},"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":34,"source":"arxiv_source","source_observed_at":"2026-05-17T23:47:56.278028Z"},"links":{"cited_paper":"/paper/2501.04871","citing_paper":"/paper/2511.08303"},"observation_digest":"sha256:94a593926b78a1047cec9d9d7b814ad43aa53f7934593590c5fe2efab7a8b1f2","observation_id":"6f7e0dfa-0528-4fab-ac0d-24828ef3cc4f","resolution":{"observed_at":"2026-05-17T23:50:31.406420Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":"2501.04871","doi":"10.48550/arxiv.2501.04871","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.04871","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Lee and Alejandro Schuler","venue":"arXiv (Cornell University)","work_id":"d22a53d9-1bab-455d-a044-90866d5b36ee","year":2025},"citing_paper":{"arxiv_id":"2604.21721","last_updated":"2026-04-23T14:24:30Z","snapshot_observed_at":"2026-08-15T20:34:53.613571Z","submitted_at":"2026-04-23T14:24:30Z","title":"A Riesz Representer Perspective on Targeted Learning","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-05-09T21:00:21.894827Z"},"links":{"cited_paper":"/paper/2501.04871","citing_paper":"/paper/2604.21721"},"observation_digest":"sha256:8c34afd94ee4fa3f0391f8ba7c2d994077b64e5582f997fb8832514d22fc2f0b","observation_id":"4e67e016-b3c1-473d-8c3c-1266fff405f0","resolution":{"observed_at":"2026-05-09T21:03:18.784236Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.04871","snapshot_observed_at":"2026-07-12T03:05:44.393410Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.03351","last_updated":"2026-07-03T14:06:54Z","snapshot_observed_at":"2026-08-12T17:10:22.552545Z","submitted_at":"2026-07-03T14:06:54Z","title":"Outcome-adapted Automatic Debiased Machine Learning","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-12T03:05:44.393410Z"},"links":{"cited_paper":"/paper/2501.04871","citing_paper":"/paper/2607.03351"},"observation_digest":"sha256:ccc262ad98e63eb24c3f82130e272d77ad702fbf274578bf65a5abc757142552","observation_id":"12c0ee15-5ef4-4463-9b45-809ce41f39ad","resolution":{"observed_at":"2026-07-12T03:05:44.393410Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.04871/citation-record","integrity":"/paper/2501.04871/integrity","json":"/paper/2501.04871/citation-record.json","paper":"/paper/2501.04871"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.561649Z","title":"Introductory Functional Analysis with Applications","venue":null,"work_id":"3f633303-f535-4975-acb1-ce39e1ce55b7","year":1989},"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":1,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.759376Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:e9d4c7c91758a4c4857110ad8d8b6e4e2f40394af0ac2570f474aaaff3967227","observation_id":"2e9f387f-a2f2-44ae-968c-5a5c578d48be","resolution":{"observed_at":"2026-08-10T21:29:08.565474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.551649Z","title":"Robins, Andrea Rotnitzky, and Lue Ping Zhao","venue":null,"work_id":"faaa054f-a9c8-46ac-87a6-38f899e1daff","year":1994},"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":2,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.764001Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:41bffb81a0bcf893c27cd00dfd05bc734644982c668a234ad188b96bec53a84c","observation_id":"9a948c9e-5a32-4f3f-bdcf-c629d6e3d31b","resolution":{"observed_at":"2026-08-10T21:29:08.555313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.541063Z","title":"Neyman’s Repeated Sampling Approach to Completely Randomized Experiments","venue":null,"work_id":"6a1e44d4-da95-442e-af00-8e1462df235f","year":2015},"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":3,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.768151Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:06d91f75584eb7c01f023a5d4f8feeaf5003b9e8b04744f3953cf7d0f5aa4d7e","observation_id":"3b579c07-decf-4142-9be0-acb92ff84bb4","resolution":{"observed_at":"2026-08-10T21:29:08.545055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.528676Z","title":"Bickel, C.A.J","venue":null,"work_id":"ecec34db-939b-421b-be44-546832513040","year":1998},"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":4,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.772713Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:b948a59907da686ec8e1e9558812f2bfcac72f28007e302bef045be2f0629503","observation_id":"3c25fb1f-230f-44f5-9b15-b774036bcbfa","resolution":{"observed_at":"2026-08-10T21:29:08.532832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.516337Z","title":"van der Laan and J.M","venue":null,"work_id":"bdeb752b-a58d-4937-8893-358dab13c8ba","year":2003},"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":5,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.776942Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:d175577942f20b9db3b9eb899defb2b93952d08f0222e968ec0bcbe6b47ef47e","observation_id":"76175793-4174-45bb-b572-e40dae7cd7d3","resolution":{"observed_at":"2026-08-10T21:29:08.519529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.506891Z","title":null,"venue":null,"work_id":"68b356e1-9dff-4eb2-8701-577b9a27e8be","year":2006},"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":6,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.780910Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:7dee81b17a77c3af9eefb1ddddc3f45bf429b68a9e7d4fe3fc16a8afa6505bc4","observation_id":"69052b61-37d2-4d23-bd7a-0a015a0b4b08","resolution":{"observed_at":"2026-08-10T21:29:08.510088Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.493347Z","title":"van der Vaart","venue":null,"work_id":"c20d9d0d-42ce-45d2-a48e-b4950d3574ae","year":2009},"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":7,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.785528Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:851c40e35fbea9d105d64666e3c1b478bd0149ffa0995fc4bb927c6cf3e18b92","observation_id":"26dd869f-8c9d-4d42-99fe-17665153d97c","resolution":{"observed_at":"2026-08-10T21:29:08.498878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:07.789169Z","title":"Newey, and Rahul Singh","venue":null,"work_id":null,"year":2022},"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":8,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.789169Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:123cf92cb48416920ec27c3e6dae23e0f04f44d1ad895981f8a59c81bfb6f68c","observation_id":"3cd270c4-2407-4ac2-91ea-65e70af3801e","resolution":{"observed_at":"2026-08-10T21:29:07.789169Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.482299Z","title":"van der Laan and Daniel Rubin","venue":null,"work_id":"1ccc4f6f-eae8-4480-9cdf-161531397b51","year":2006},"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":9,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.793585Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:1775cafa626a94fdbd6704120fd9e641cb81565bb973ba45bc5fbd48df8f9a4e","observation_id":"b28e401b-2d0a-48b3-a45b-761c152eddc4","resolution":{"observed_at":"2026-08-10T21:29:08.485906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.06135","last_updated":"2024-10-24T18:05:34Z","snapshot_observed_at":"2026-08-14T07:10:52.567161Z","submitted_at":"2024-05-09T23:04:16Z","title":"Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.06135","snapshot_observed_at":"2026-08-10T21:29:07.797146Z","title":"Williams, Kara E","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":10,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.797146Z"},"links":{"cited_paper":"/paper/2405.06135","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:775424fafc79507852b46ade1557bc6c1fc0db770b21d503afc17ed642afa228","observation_id":"78a55b26-f6ea-4d01-943d-34367bd5ef43","resolution":{"observed_at":"2026-08-10T21:29:07.797146Z","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":"2110.03031","last_updated":"2022-06-15T08:31:10Z","snapshot_observed_at":"2026-07-06T11:55:07.535343Z","submitted_at":"2021-10-06T19:29:20Z","title":"RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.03031","snapshot_observed_at":"2026-08-10T21:29:07.806231Z","title":"Newey, Victor Quintas-Martinez, and Vasilis Syrgka- nis","venue":null,"work_id":null,"year":2022},"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":12,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.806231Z"},"links":{"cited_paper":"/paper/2110.03031","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:e10ee9a71141dd8ab924c510cd850b397f9eb7e48659e4fc61c5b9d7c0809020","observation_id":"2e4e918d-5fbf-48b4-a209-fe334dce1e96","resolution":{"observed_at":"2026-08-10T21:29:07.806231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14831","last_updated":"2021-10-28T00:51:16Z","snapshot_observed_at":"2026-08-16T04:57:27.625854Z","submitted_at":"2021-10-28T00:51:16Z","title":"The Balancing Act in Causal Inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14831","snapshot_observed_at":"2026-08-10T21:29:07.811813Z","title":"Hirshberg, and Jos´ e R","venue":null,"work_id":null,"year":2021},"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":13,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.811813Z"},"links":{"cited_paper":"/paper/2110.14831","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:991ca45d2dfa22e83e5bbdbb075c1e98ac04d87b798b6e1bbea09776a574cc23","observation_id":"959be986-1186-4828-8678-1a240ad59077","resolution":{"observed_at":"2026-08-10T21:29:07.811813Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.470465Z","title":"Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies","venue":null,"work_id":"f21d7563-f947-4bd8-88d1-b219c788c148","year":2012},"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":14,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.816241Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:f3b0631d6fd6d4422dc45b9fe0b2cc45c40a01ed399edc5ee0ae3839f97e47ec","observation_id":"41de0f3c-bcbf-4457-8025-a20f541c0fa1","resolution":{"observed_at":"2026-08-10T21:29:08.474955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.459927Z","title":"Graham, Cristine Campos De Xavier Pinto, and Daniel Egel","venue":null,"work_id":"b83ef3b8-b15d-4c36-ab50-4ae35aa3a1db","year":2012},"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":15,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.819624Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:65049ed714c80cee23fcc294c1189a8daeaff9b34ae959d5ddc754ac39a1d00c","observation_id":"b27eb44b-fd32-4390-a736-281240e6df1d","resolution":{"observed_at":"2026-08-10T21:29:08.463884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:07.822931Z","title":"Zubizarreta","venue":null,"work_id":null,"year":2015},"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":16,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.822931Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:b8ae32f3c38c8ff9ac6dea62159724347b94cf8839a5e2c56e5e5d3b5410d2ae","observation_id":"9f785b99-57fd-4ef4-9840-a52af5491929","resolution":{"observed_at":"2026-08-10T21:29:07.822931Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.06581","last_updated":"2022-07-07T13:39:33Z","snapshot_observed_at":"2026-08-13T19:40:15.686649Z","submitted_at":"2021-04-14T01:57:12Z","title":"On the implied weights of linear regression for causal inference","version":4},"cited_work":{"arxiv_id":"2104.06581","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.06581","snapshot_observed_at":"2026-08-10T21:29:08.148470Z","title":"On the implied weights of linear regression for causal inference","venue":"stat.ME","work_id":"b2ede026-6680-4d11-bfeb-182ef9177a8d","year":2021},"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":17,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.826246Z"},"links":{"cited_paper":"/paper/2104.06581","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:3362fce865627f8f2ffb161a219f47acf4934cf6e2404e97c739696d0d1f71dd","observation_id":"d23020bb-a57f-4fa7-81f7-7545189f7cda","resolution":{"observed_at":"2026-08-10T21:29:08.154941Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.448958Z","title":"Friedman","venue":null,"work_id":"e1523089-2604-4aeb-9987-00490ac4f14c","year":2001},"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":18,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.830233Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:47efb1671a3a3daa2f4d2fa80b945f15b90b7e89ac45f565f59659b3cc34e2fe","observation_id":"272a69e5-4e08-42e4-9344-042ba301fe16","resolution":{"observed_at":"2026-08-10T21:29:08.452669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.437023Z","title":"An empirical comparison of supervised learning algorithms","venue":null,"work_id":"9647041a-a598-42bf-a701-a53e228a4921","year":2006},"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":19,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.833559Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:b67be82fdae5acd28148f7878b97909aa7db8a38dc575ab4e25353dd412769c2","observation_id":"33c922e9-a221-44c5-a81d-26c01c9180e9","resolution":{"observed_at":"2026-08-10T21:29:08.441075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.424260Z","title":"XGBoost: A Scalable Tree Boosting System","venue":null,"work_id":"bbc6dc23-3692-4f2e-a2a7-65cc9bd8f796","year":2016},"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":20,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.836911Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:c559c8e82505bf93eeb8a6f7f119ce3f9b71d7071d99c67e97f78013cc85d3d3","observation_id":"5d8c7c8b-dd83-44c1-815e-763681c546d6","resolution":{"observed_at":"2026-08-10T21:29:08.428621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.413116Z","title":"LightGBM: A Highly Efficient Gradient Boosting Decision Tree","venue":null,"work_id":"a1dd0925-1f1b-4eb6-ae6c-5bb4938d7882","year":2017},"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":21,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.840619Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:487691959235d61f826f39a9b019e10b9bcb954fdeea15eb727fdc10f6cda455","observation_id":"34fb44fc-438c-4ddd-a879-083c9ac7c672","resolution":{"observed_at":"2026-08-10T21:29:08.417991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.403054Z","title":"Tabular data: Deep learning is not all you need","venue":null,"work_id":"5b02bb61-1197-41a6-bbee-a95116e6c803","year":2022},"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":22,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.843779Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:ce707fb4e52b5a7c0715339aeebad32672234c155d39b28139593a4b24260390","observation_id":"15c8a5c4-cde5-4ec3-a20a-9b6e12551bf3","resolution":{"observed_at":"2026-08-10T21:29:08.406625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.02997","last_updated":"2024-07-15T19:00:47Z","snapshot_observed_at":"2026-08-15T05:32:25.576258Z","submitted_at":"2023-05-04T17:04:41Z","title":"When Do Neural Nets Outperform Boosted Trees on Tabular Data?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.02997","snapshot_observed_at":"2026-08-10T21:29:07.846835Z","title":"When Do Neural Nets Outperform Boosted Trees on Tabular Data?, July 2024","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":23,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.846835Z"},"links":{"cited_paper":"/paper/2305.02997","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:b83145949a07cbe72816f19116c03e6f669ff378be4b737c5034b39203a74b05","observation_id":"7a69160c-b3e1-406b-8721-9f26edd5e9d0","resolution":{"observed_at":"2026-08-10T21:29:07.846835Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.391455Z","title":"Deep Neural Networks and Tabular Data: A Survey","venue":null,"work_id":"58cf4d77-5234-4709-b8d1-6a33394c3a3b","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":24,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.851049Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:d963413772dd276fde5b8127998cdc50f9022da279fc7a331476093fa74263b6","observation_id":"d7ab311d-c648-4a15-9ec2-8ecdee3c9bd0","resolution":{"observed_at":"2026-08-10T21:29:08.395090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.380883Z","title":"Friedman","venue":null,"work_id":"64624836-82ec-495d-ba39-206b4b250940","year":2002},"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":25,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.854175Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:471b8644119ba9acdd279a80c35b36fdd00eeda79fd537b99fcc1ef4a3a0d7a6","observation_id":"96dd116f-bf01-4c1d-acd4-7edb9dbd722b","resolution":{"observed_at":"2026-08-10T21:29:08.384414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:07.857449Z","title":"Population Intervention Causal Effects Based on Stochastic Interventions","venue":null,"work_id":null,"year":2012},"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":26,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.857449Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:2817ce827a9346d4366a77e9eec3da8d16d20adee7aa291261aadd54d7ed28c7","observation_id":"799c5028-fc84-4991-9163-59f027317ff3","resolution":{"observed_at":"2026-08-10T21:29:07.857449Z","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":"2026-08-10T21:29:07.861431Z","title":"Hoffman, and Edward J","venue":null,"work_id":null,"year":2023},"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":27,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.861431Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:7cddd970b332f0bf1d4d69c7f2d8766a1a0d7115a0848a44e04c27badccb98d7","observation_id":"ede22892-1ce4-40cf-aada-6d792a960cc4","resolution":{"observed_at":"2026-08-10T21:29:07.861431Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.369816Z","title":"Asymptotic Theory for Cross-validated Tar- geted Maximum Likelihood Estimation","venue":null,"work_id":"1c044a27-257b-447c-a013-93f42dedb0fd","year":2010},"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":28,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.865105Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:af5ec430a34b689d19bd4635cdcdb14fd1605fd393d396a53f834e590a9b9f7b","observation_id":"29dfe643-eb2c-4bf1-807c-c06d3045b715","resolution":{"observed_at":"2026-08-10T21:29:08.374085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.359053Z","title":"Double/debiased machine learning for treatment and structural parameters","venue":null,"work_id":"b76f470f-6238-4015-a15b-44b167afeb0a","year":2018},"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":29,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.869227Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:a7b253059cc1eb538be70e9b08550237ee243203abe0b68e458eff3619e5529b","observation_id":"eb243796-da65-4c9c-af3c-f2fcc7f3188f","resolution":{"observed_at":"2026-08-10T21:29:08.362869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.11076","last_updated":"2024-07-04T20:09:15Z","snapshot_observed_at":"2026-08-12T17:10:42.413218Z","submitted_at":"2021-02-22T14:46:23Z","title":"Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.11076","snapshot_observed_at":"2026-08-10T21:29:07.872683Z","title":"Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension, July 2024","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":30,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.872683Z"},"links":{"cited_paper":"/paper/2102.11076","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:fd3188bf1586ddc6b98905c95bc9ae6b84afdc6d2fa7934fb5083c6eb08800d3","observation_id":"82e70ca4-ae41-4fa7-8bf0-be885442658e","resolution":{"observed_at":"2026-08-10T21:29:07.872683Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.346148Z","title":"Smoothing noisy data with spline functions","venue":null,"work_id":"37dc1077-d18e-429d-829d-63ca1a29be52","year":1978},"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":31,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.876825Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:7d686a019a7f7362e227c0c44447f3d5f05bcb8c21fb2b3f3c12b719ce412ca5","observation_id":"eac2ca7c-7730-4527-87c1-13239157563b","resolution":{"observed_at":"2026-08-10T21:29:08.350893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.333113Z","title":"Tibshirani","venue":null,"work_id":"433a04a9-a905-462b-9478-9fc6f285fd1f","year":2016},"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":32,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.880301Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:75aeeb233bb0936ce37530a994a5e7f05cb58d3cd84a8da38795b1db8b6f3ad7","observation_id":"feabfd17-5cdd-4ef2-9810-857e7b2a8771","resolution":{"observed_at":"2026-08-10T21:29:08.337221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.321324Z","title":"Boosting with early stopping: Convergence and consistency","venue":null,"work_id":"06c341c5-8c4c-4e4a-8d13-3388d6fbce1e","year":2005},"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":33,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.884049Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:253a77d9ca8b1ad2b7eba8ba2bf53e0be62f92f779eaf1b7da7d84e9b3aa8c96","observation_id":"24cc7773-15d5-47cc-8f3e-1b94f482ce71","resolution":{"observed_at":"2026-08-10T21:29:08.325584Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.309293Z","title":"Lassoed Tree Boosting, December","venue":null,"work_id":"f952d36b-62d7-48c1-910a-7c489a7d845a","year":null},"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":34,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.887637Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:3e8f549b926349e0270c2ad596817d0eee6abcc044292529afde64f9c1a47273","observation_id":"90544ba8-d2d8-4963-a204-c56c41321ca4","resolution":{"observed_at":"2026-08-10T21:29:08.313695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.297813Z","title":"van der Laan","venue":null,"work_id":"81b31bb7-926a-490a-b9b6-a7f389d6e70e","year":null},"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":35,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.894963Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:61ad9162896af81796c0f635e2e2236cd9ab6a616e961a2bd080a912e6694656","observation_id":"c57c490e-e4bc-413c-921b-189e46c4fa02","resolution":{"observed_at":"2026-08-10T21:29:08.301372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:29:08.286253Z","title":"1q. Therefore, to derive the EIF, we must take this dependency into consideration (e.g. using the delta method on the inverse probability parameter 1 PpA“1q and the “partial","venue":null,"work_id":"3a5f4f5d-7544-43c3-9628-18d490539d5b","year":2011},"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":36,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.899920Z"},"links":{"citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:9c9c5216ef4c1f0e9329cd73add9c0691d40c56b3a3056a4f2b8b6c3ae237b9b","observation_id":"76880ea1-3c83-4e77-a1be-e846a6dd176b","resolution":{"observed_at":"2026-08-10T21:29:08.290378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10697","last_updated":"2023-12-08T19:39:57Z","snapshot_observed_at":"2026-08-13T15:39:32.713062Z","submitted_at":"2022-05-22T00:34:41Z","title":"Lassoed Tree Boosting","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10697","snapshot_observed_at":"2026-08-10T21:29:07.891060Z","title":null,"venue":null,"work_id":null,"year":null},"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":2023,"source":"pdf_text","source_observed_at":"2026-08-10T21:29:07.891060Z"},"links":{"cited_paper":"/paper/2205.10697","citing_paper":"/paper/2501.04871"},"observation_digest":"sha256:0fab642f0e2bf7d47c93b2078be0b13f99f7f76f83d3d596ea8c0746d3b7a711","observation_id":"ec6e5174-7ea9-4cfe-88e8-377d9cd9c876","resolution":{"observed_at":"2026-08-10T21:29:07.891060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.04871","last_updated":"2025-02-04T22:04:32Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-12T17:09:55.473781Z","submitted_at":"2025-01-08T23:04:32Z","title":"RieszBoost: Gradient Boosting for Riesz Regression"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":24},"total_outbound_references":37},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2501.04871."}