{"as_of":"2026-08-14T17:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c416cc49d2d5e49760ae913f56d8c134c878d9c0ca253784179e64d92cf8f5ab","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:43:58.546929Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T10:57:43.761067Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.06317","last_updated":"2022-06-16T00:15:19Z","snapshot_observed_at":"2026-08-13T16:42:14.673209Z","submitted_at":"2022-02-13T14:00:09Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.06317","snapshot_observed_at":"2026-08-12T17:43:58.546929Z","title":"Off-policy evaluation for larg e action spaces via embeddings","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12786","last_updated":"2024-11-19T10:18:27Z","snapshot_observed_at":"2026-08-13T18:02:51.254768Z","submitted_at":"2024-11-19T10:18:27Z","title":"Off-policy estimation with adaptively collected data: the power of online learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T17:43:58.546929Z"},"links":{"cited_paper":"/paper/2202.06317","citing_paper":"/paper/2411.12786"},"observation_digest":"sha256:ab2da2650b18814da4b334ede42c2551de4cb3ebf57ab85a2a4017795e7f5bb8","observation_id":"7dcc1f49-cef1-4b27-a663-9803d30b5ea5","resolution":{"observed_at":"2026-08-12T17:43:58.546929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.06317","last_updated":"2022-06-16T00:15:19Z","snapshot_observed_at":"2026-08-13T16:42:14.673209Z","submitted_at":"2022-02-13T14:00:09Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.06317","snapshot_observed_at":"2026-08-06T18:32:38.498669Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.07909","last_updated":"2025-07-10T16:41:10Z","snapshot_observed_at":"2026-08-12T03:28:11.653798Z","submitted_at":"2025-07-10T16:41:10Z","title":"Document Similarity Enhanced IPS Estimation for Unbiased Learning to Rank","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T18:32:38.498669Z"},"links":{"cited_paper":"/paper/2202.06317","citing_paper":"/paper/2507.07909"},"observation_digest":"sha256:78648aa599593f67e7422cc92e34ae95e7bcbcaae317c28f9b393b5174c94856","observation_id":"e9b43e8b-e062-4608-b63c-dda919e44cb7","resolution":{"observed_at":"2026-08-06T18:32:38.498669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.06317","last_updated":"2022-06-16T00:15:19Z","snapshot_observed_at":"2026-08-13T16:42:14.673209Z","submitted_at":"2022-02-13T14:00:09Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.06317","snapshot_observed_at":"2026-08-06T16:28:50.166162Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.13608","last_updated":"2025-07-18T02:23:37Z","snapshot_observed_at":"2026-08-12T22:19:05.078391Z","submitted_at":"2025-07-18T02:23:37Z","title":"Off-Policy Evaluation and Learning for Matching Markets","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:28:50.166162Z"},"links":{"cited_paper":"/paper/2202.06317","citing_paper":"/paper/2507.13608"},"observation_digest":"sha256:43dd4578363c89ac0caf08aa630ac49c39964c5d82d28ecfa2466db1e928b0e0","observation_id":"527a415b-70c6-4636-9a71-3d2ba77fb540","resolution":{"observed_at":"2026-08-06T16:28:50.166162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.06317","last_updated":"2022-06-16T00:15:19Z","snapshot_observed_at":"2026-08-13T16:42:14.673209Z","submitted_at":"2022-02-13T14:00:09Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings","version":2},"cited_work":{"arxiv_id":"2202.06317","doi":null,"metadata_source":"pith","pith_arxiv_id":"2202.06317","snapshot_observed_at":"2026-08-05T10:57:43.761067Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings","venue":"cs.LG","work_id":"e8a2cdbb-9f04-4c97-9ea0-e30ffcd0d469","year":2022},"citing_paper":{"arxiv_id":"2509.03456","last_updated":"2026-06-01T12:41:06Z","snapshot_observed_at":"2026-08-10T13:17:48.639224Z","submitted_at":"2025-09-03T16:25:45Z","title":"Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T10:57:43.694393Z"},"links":{"cited_paper":"/paper/2202.06317","citing_paper":"/paper/2509.03456"},"observation_digest":"sha256:f8debd24418d74ae804e30abdbf028dbff11aa6aa910c007be8d215748d91d46","observation_id":"bcd1a46c-dd02-4fcb-9d8d-79e2bd53c67a","resolution":{"observed_at":"2026-08-05T10:57:43.766116Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2202.06317/citation-record","integrity":"/paper/2202.06317/integrity","json":"/paper/2202.06317/citation-record.json","paper":"/paper/2202.06317"},"outbound":[],"paper":{"arxiv_id":"2202.06317","last_updated":"2022-06-16T00:15:19Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T16:42:14.673209Z","submitted_at":"2022-02-13T14:00:09Z","title":"Off-Policy Evaluation for Large Action Spaces via Embeddings"},"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 4 inbound Pith citation observations for arXiv:2202.06317."}