{"as_of":"2026-08-19T14:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3d66429257a7a68d1d5ea15ca2f5580ee78f41c4196709f94a079e137f150f72","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T10:38:15.385044Z","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":"2026-07-04T13:29:50.858348Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2604.14352","last_updated":"2026-04-15T19:10:53Z","snapshot_observed_at":"2026-08-14T07:30:59.255893Z","submitted_at":"2026-04-15T19:10:53Z","title":"PROXIMA: A Reliability Scoring Framework for Proxy Metrics in Online Controlled Experiments","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-10T12:21:01.000036Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2604.14352"},"observation_digest":"sha256:36f3591fbaa8afaee0b88fe332ae4fbd36e3936275633cf93cd35694c7b6fc3d","observation_id":"f38ce8ec-f7fc-40cb-9c52-23a869752917","resolution":{"observed_at":"2026-05-10T12:25:22.756128Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2605.07065","last_updated":"2026-05-08T00:17:15Z","snapshot_observed_at":"2026-08-16T04:56:07.334029Z","submitted_at":"2026-05-08T00:17:15Z","title":"Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-05-11T01:39:50.275352Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2605.07065"},"observation_digest":"sha256:4506a734e8ad58866cf09d96acb198f689f45a784af290cd845974850f381b7a","observation_id":"64b81461-f47a-4ee7-b0e9-f85edb257c5b","resolution":{"observed_at":"2026-05-11T01:40:51.688449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2605.10430","last_updated":"2026-05-23T09:40:21Z","snapshot_observed_at":"2026-08-16T05:57:16.104766Z","submitted_at":"2026-05-11T12:04:02Z","title":"Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation","version":1},"reference_index":109,"source":"arxiv_source","source_observed_at":"2026-05-12T04:38:31.839273Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2605.10430"},"observation_digest":"sha256:2e87ef56524996cc8089955d1d32efd7ae0394038aea47f44cc2c8ab017bb317","observation_id":"31295b37-5d98-488f-8c6b-8265d4e9cb7b","resolution":{"observed_at":"2026-05-12T06:01:26.270104Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2605.10430","last_updated":"2026-05-23T09:40:21Z","snapshot_observed_at":"2026-08-16T05:57:16.104766Z","submitted_at":"2026-05-11T12:04:02Z","title":"Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T22:07:52.178431Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2605.10430"},"observation_digest":"sha256:905a3a5d8cd294b681ced36d592b221358665aab308f62d9af8c25da4c7310a2","observation_id":"715a7141-8e10-496e-98ff-03c7d1c746a4","resolution":{"observed_at":"2026-07-01T14:15:47.383871Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2606.03878","last_updated":"2026-06-02T16:46:38Z","snapshot_observed_at":"2026-08-15T01:45:26.663754Z","submitted_at":"2026-06-02T16:46:38Z","title":"Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T07:56:52.775722Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2606.03878"},"observation_digest":"sha256:38e9ca334c67c4c953e46c1b484c1ebf8f52e40a5905d884bf97df98b21b33e9","observation_id":"eb927266-5d3c-4fdd-9f59-ab82c328e7c3","resolution":{"observed_at":"2026-07-02T05:56:40.497746Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":"2111.10106","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-07-04T13:29:50.858348Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":"6a457a73-1ee3-40de-9dca-9b69cc359d0f","year":2021},"citing_paper":{"arxiv_id":"2606.27114","last_updated":"2026-06-25T14:49:50Z","snapshot_observed_at":"2026-08-06T22:59:29.445064Z","submitted_at":"2026-06-25T14:49:50Z","title":"Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-26T05:14:37.758306Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2606.27114"},"observation_digest":"sha256:70a99f63e10ed7ed7fea2c59489ddc71dd7fb96519727637a653417054cc3509","observation_id":"6e51d095-f653-4019-a587-36e74e3e31ca","resolution":{"observed_at":"2026-07-04T13:29:50.860603Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.10106","snapshot_observed_at":"2026-08-14T10:38:15.385044Z","title":"arXiv preprint arXiv:2111.10106 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.13461","last_updated":"2026-08-13T16:44:08Z","snapshot_observed_at":"2026-08-18T12:30:32.155486Z","submitted_at":"2026-08-13T16:44:08Z","title":"Doubly Robust Estimation of Causal Effect on CVR with Targeted Regularization","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-14T10:38:15.385044Z"},"links":{"cited_paper":"/paper/2111.10106","citing_paper":"/paper/2608.13461"},"observation_digest":"sha256:63eaaeea15fa5f4fd464f154f31e4af51a805d246948faeb58f3889b12022c2c","observation_id":"dfb11770-e772-4f28-be58-e5ddd22c2f2b","resolution":{"observed_at":"2026-08-14T10:38:15.385044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2111.10106/citation-record","integrity":"/paper/2111.10106/integrity","json":"/paper/2111.10106/citation-record.json","paper":"/paper/2111.10106"},"outbound":[],"paper":{"arxiv_id":"2111.10106","last_updated":"2021-11-19T09:07:14Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-17T14:08:20.394101Z","submitted_at":"2021-11-19T09:07:14Z","title":"A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2111.10106."}