{"as_of":"2026-08-09T03:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a131be8dc4bba54075d594d86314768a4fb4d8a633dee6ef82b7cd78d039940d","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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":"2026-08-06T10:29:39.217363Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-15T03:09:43.469388Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2009.13447","last_updated":"2021-08-27T16:28:01Z","snapshot_observed_at":"2026-07-06T09:59:29.017085Z","submitted_at":"2020-09-28T16:12:38Z","title":"Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.13447","snapshot_observed_at":"2026-08-06T10:29:39.217363Z","title":"Why Resampling Outperforms Reweighting for Correcting Sampling Bias with Stochastic Gradients,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.00089","last_updated":"2025-08-07T04:25:14Z","snapshot_observed_at":"2026-08-06T10:29:36.270303Z","submitted_at":"2025-07-31T18:36:44Z","title":"Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples","version":2},"reference_index":1997,"source":"pdf_text","source_observed_at":"2026-08-06T10:29:39.217363Z"},"links":{"cited_paper":"/paper/2009.13447","citing_paper":"/paper/2508.00089"},"observation_digest":"sha256:d47da959664611454fc75f5c6a0551b1e4364d12dfe32546323f2248517a7493","observation_id":"ae3f0d36-ed05-41d7-a7f1-a71237f4e5f4","resolution":{"observed_at":"2026-08-06T10:29:39.217363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.13447","last_updated":"2021-08-27T16:28:01Z","snapshot_observed_at":"2026-07-06T09:59:29.017085Z","submitted_at":"2020-09-28T16:12:38Z","title":"Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.13447","snapshot_observed_at":"2026-08-05T18:23:19.980854Z","title":"Why resampling outperforms reweighting for correcting sam- pling bias with stochastic gradients","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2508.14741","last_updated":"2025-08-20T14:40:21Z","snapshot_observed_at":"2026-08-08T17:04:21.222931Z","submitted_at":"2025-08-20T14:40:21Z","title":"CaTE Data Curation for Trustworthy AI","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T18:23:19.980854Z"},"links":{"cited_paper":"/paper/2009.13447","citing_paper":"/paper/2508.14741"},"observation_digest":"sha256:7bb7ec63f8a35700be1142ec5257af1c3118c58c033ed3f6687e40eff49b34ed","observation_id":"b8d0406d-1fb3-46c2-ac2e-4ff9948f5fef","resolution":{"observed_at":"2026-08-05T18:23:19.980854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.13447","last_updated":"2021-08-27T16:28:01Z","snapshot_observed_at":"2026-07-06T09:59:29.017085Z","submitted_at":"2020-09-28T16:12:38Z","title":"Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients","version":3},"cited_work":{"arxiv_id":"2009.13447","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2009.13447","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2009.13447 , year=","venue":null,"work_id":"adacbe42-98ab-4567-bf8d-c61c67fa504a","year":2009},"citing_paper":{"arxiv_id":"2605.14350","last_updated":"2026-05-14T04:22:24Z","snapshot_observed_at":"2026-07-06T23:25:49.545418Z","submitted_at":"2026-05-14T04:22:24Z","title":"Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling","version":1},"reference_index":243,"source":"arxiv_source","source_observed_at":"2026-05-15T03:05:36.871497Z"},"links":{"cited_paper":"/paper/2009.13447","citing_paper":"/paper/2605.14350"},"observation_digest":"sha256:06326634d21a523a2e4c433396dd9e9bb5d93bdd0fe96f088f66459c284ce981","observation_id":"483c917e-0cdd-48cd-938c-2a977c3ad023","resolution":{"observed_at":"2026-05-15T03:09:43.472297Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2009.13447/citation-record","integrity":"/paper/2009.13447/integrity","json":"/paper/2009.13447/citation-record.json","paper":"/paper/2009.13447"},"outbound":[],"paper":{"arxiv_id":"2009.13447","last_updated":"2021-08-27T16:28:01Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T09:59:29.017085Z","submitted_at":"2020-09-28T16:12:38Z","title":"Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2009.13447."}