{"as_of":"2026-08-10T10:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5df7398e183e02c96cbf4de77e3084f30dbc45ad4c63fd47832f366c9a798ee6","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:33:18.029095Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.02762/citation-record","integrity":"/paper/2507.02762/integrity","json":"/paper/2507.02762/citation-record.json","paper":"/paper/2507.02762"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:22.373590Z","title":"Improved algorithms for linear stochastic bandits","venue":null,"work_id":"b1c6dcdc-e796-4c55-895f-d385e128c677","year":2011},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.292650Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:c59d3e292a2041d9af4b642b8a83f63fa2a5a70ef9a76a19b268b5b2268a3da3","observation_id":"9e49f02e-7ff1-4940-88b6-6a80d5d310c5","resolution":{"observed_at":"2026-08-06T20:33:22.378122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.358763Z","title":"Personalized dynamic pricing with machine learning: High- dimensional features and heterogeneous elasticity","venue":null,"work_id":"7d4d1911-512c-4710-b564-3b8278dd6bcd","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.396229Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:bc6caa5ba2e3d54a08bddb786c3926ad8443988a896827af0b1fdd108120497a","observation_id":"82117a78-e902-4950-abc9-f4bc0ba9b9e9","resolution":{"observed_at":"2026-08-06T20:33:22.363422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.331258Z","title":"High-probability regret bounds for bandit online linear optimization","venue":null,"work_id":"6d586d6e-173a-4b1d-a3ec-d47539ae72b9","year":2008},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.626768Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:84aeb788869c65bf3ec1f8d880d801af7e05be86825e2eab9934dd83a528e945","observation_id":"56c84f51-62a6-43dd-ba49-5c214af2e00e","resolution":{"observed_at":"2026-08-06T20:33:22.335460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.317226Z","title":"Meta dynamic pricing: Transfer learning across experiments","venue":null,"work_id":"7ac60dc1-cfa0-491a-a6fc-dd6da040c556","year":2022},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.797065Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:bad9cb697ce9575f6b1525f4ee72e680529000f3d5ed19a8b6a4be2778f07294","observation_id":"50709f0f-f82d-4ea8-b849-8f07252b99d6","resolution":{"observed_at":"2026-08-06T20:33:22.321434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.302538Z","title":"Robust wasserstein profile inference and applications to machine learning","venue":null,"work_id":"8d133844-dfc9-4c30-9660-3d293af4a639","year":2019},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.961663Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:f1404ad42febd8bdd8c66ba7769186a55c588931a115310254f6f924561dca77","observation_id":"30e01027-4e19-49f8-ac23-b624b952b9ca","resolution":{"observed_at":"2026-08-06T20:33:22.307092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.289387Z","title":"Online pricing with offline data: Phase transition and inverse square law","venue":null,"work_id":"e211a19f-69f1-4ef0-8ae5-e3dbbcc3aeb9","year":2020},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.063414Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:f99c6d1e78feffcf9bb9bcdeeb6df01d5f957b21775a5d967dc7f89bc60513c8","observation_id":"de0de28f-ca15-43dc-8c7c-e5d8cd8b0816","resolution":{"observed_at":"2026-08-06T20:33:22.293449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2408.12136","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:19.006150Z","title":"Domain adaptation for offline rein- forcement learning with limited samples","venue":null,"work_id":"00108fb7-a15a-4c74-8bd6-ac56bd0027e6","year":2024},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.182477Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:6732de930e516d8e339e067427e8bf622ef88b97d433282f4eed83a0188d8e0f","observation_id":"02e46d47-9d87-4faa-aad5-c04aba59dd28","resolution":{"observed_at":"2026-08-06T20:33:19.042819Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.08998","last_updated":"2022-11-16T15:52:49Z","snapshot_observed_at":"2026-08-10T02:00:59.752741Z","submitted_at":"2022-11-16T15:52:49Z","title":"Data-pooling Reinforcement Learning for Personalized Healthcare Intervention","version":1},"cited_work":{"arxiv_id":"2211.08998","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.08998","snapshot_observed_at":"2026-08-06T20:33:18.749969Z","title":"Data-pooling Reinforcement Learning for Personalized Healthcare Intervention","venue":"cs.LG","work_id":"ced45ed1-ccfb-4dd6-8de9-167af21b3121","year":2022},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.308409Z"},"links":{"cited_paper":"/paper/2211.08998","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:53ad488f2cff5ab035aeef69b31786542a6f58073dd6bcf7f6a145c13a68491e","observation_id":"6c7620ff-a42b-45f9-861c-e7b7decfc06e","resolution":{"observed_at":"2026-08-06T20:33:18.850964Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:15.420244Z","title":"Leveraging (biased) information: Multi-armed bandits with offline data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.420244Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:1afebe327062c235c715b27da81ee48d807cb073a72b35af6073a7af844a62dc","observation_id":"91abbdf9-b803-485f-8a5c-c38a3cf739a0","resolution":{"observed_at":"2026-08-06T20:33:15.420244Z","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":"2026-08-06T20:33:22.275829Z","title":"Feature-based dynamic pricing","venue":null,"work_id":"725e6643-a981-4c89-9861-f03a5074c9f8","year":2020},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.538979Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:5f7b123333554896eb4b99ad0eba258466396c515f9672071b2c4cfbcb01b2fe","observation_id":"95b1a160-0426-4461-820d-101920914b7d","resolution":{"observed_at":"2026-08-06T20:33:22.280110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.13916","last_updated":"2021-04-14T23:38:31Z","snapshot_observed_at":"2026-07-06T09:32:26.221291Z","submitted_at":"2020-06-24T17:47:37Z","title":"Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.13916","snapshot_observed_at":"2026-08-06T20:33:15.689811Z","title":"Off-dynamics reinforcement learning: Training for transfer with domain classifiers","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.689811Z"},"links":{"cited_paper":"/paper/2006.13916","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:69a8f67c3ed8a45c50a0cf1a9e6691f1d7c00c4c16e9b564d35349f96f27ea3e","observation_id":"2ae15d6c-b760-4c6d-b9a5-4477e796257f","resolution":{"observed_at":"2026-08-06T20:33:15.689811Z","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":"2026-08-06T20:33:22.261779Z","title":"A tail inequality for quadratic forms of subgaussian random vectors","venue":null,"work_id":"e977b9b9-f525-406c-86c7-15cb6ecfc124","year":2012},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.741630Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:21183e99c92c0220a968c2ce0d8cda77e3c17d114aac7fb9faffe216f54c5ec6","observation_id":"b880b5bb-363c-462f-9dd3-5b01f5e712c3","resolution":{"observed_at":"2026-08-06T20:33:22.266371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.247313Z","title":"Dynamic pricing with an unknown demand model: Asymp- totically optimal semi-myopic policies","venue":null,"work_id":"be251917-3053-41c2-b1ca-7dad10976cee","year":2014},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.791670Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:349d728d5d602246301e7800d4516adf74ce89c62d7a57a3d5beda513f08b09c","observation_id":"29b020e7-6adc-4c17-a813-bb4d0c953023","resolution":{"observed_at":"2026-08-06T20:33:22.251803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.233164Z","title":"Meta-thompson sampling","venue":null,"work_id":"52fefd4b-677b-42b5-8ee6-0e757d8d53fd","year":2021},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.902986Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:6bc055c1d11e8c9a804ae15ee3b4aa1f5696fb784a2ef106250034bd3e337e6a","observation_id":"9a630113-495d-413e-9ffd-ed4e28071da3","resolution":{"observed_at":"2026-08-06T20:33:22.237951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.219704Z","title":"Bandit algorithms","venue":null,"work_id":"8b018aed-1095-427c-93f3-fbf41e3555cb","year":2020},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:15.980929Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:e91ba4aa66087c11dce3ffdca86f2c01570b87c38742790dd4cdbb1470d8401c","observation_id":"28907ca3-08dc-4762-8a8e-00d447d993ef","resolution":{"observed_at":"2026-08-06T20:33:22.224173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.205979Z","title":"Dynamic pricing with external information and inventory constraint","venue":null,"work_id":"847291c8-0e55-4b51-b163-5778a6e72c58","year":2024},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.039706Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:19c276f414152c9b62f394775ceace0bc38afd779a2bbfbfa5a1ae2db1259177","observation_id":"3c6678c7-3d02-42da-8141-606a9fceabc8","resolution":{"observed_at":"2026-08-06T20:33:22.210291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.191875Z","title":"On the prior sensitivity of thompson sampling","venue":null,"work_id":"719d963c-48cc-46c6-ade1-74ba9dba45f8","year":2016},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.130899Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:7edb9feb6ed2e5c61baa5f11f3be93d3438ae2dc0ff4c6301b3ea8df33d93165","observation_id":"fb91acca-aeda-4baf-8c7d-e57c17f05c30","resolution":{"observed_at":"2026-08-06T20:33:22.196219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1604.07463","last_updated":"2016-04-25T22:22:11Z","snapshot_observed_at":"2026-08-06T04:05:36.933493Z","submitted_at":"2016-04-25T22:22:11Z","title":"Dynamic Pricing with Demand Covariates","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1604.07463","snapshot_observed_at":"2026-08-06T20:33:16.211815Z","title":"Dynamic pricing with demand covariates","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.211815Z"},"links":{"cited_paper":"/paper/1604.07463","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:7a7fe53e7e001029af995c2e80ee5fca479cb87d7259927d729971db0616a150","observation_id":"a3472ab5-ee9c-428c-b205-187fc4ce7085","resolution":{"observed_at":"2026-08-06T20:33:16.211815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.03810","last_updated":"2024-11-06T10:14:46Z","snapshot_observed_at":"2026-07-06T19:46:06.343310Z","submitted_at":"2024-11-06T10:14:46Z","title":"Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.03810","snapshot_observed_at":"2026-08-06T20:33:16.277113Z","title":"Hybrid transfer reinforcement learning: Provable sample efficiency from shifted-dynamics data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.277113Z"},"links":{"cited_paper":"/paper/2411.03810","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:73e60df6d947f7e47c9554ced3fc46ea6f299890381c7df160a8beb0f631800f","observation_id":"4b460ac1-c88b-40fe-b4af-f5bbd26668f9","resolution":{"observed_at":"2026-08-06T20:33:16.277113Z","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":"2026-08-06T20:33:22.176994Z","title":"Online learning with predictable sequences","venue":null,"work_id":"a5fc29c8-0e93-4f55-a3fc-448c9c6e40f5","year":2013},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.341937Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:efbe5bdbf655920d9638dadf56937e16556838e0bcce079ce1c56c123b071b03","observation_id":"825b5a54-f314-48a2-92e7-9b794e5b8ffb","resolution":{"observed_at":"2026-08-06T20:33:22.182204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.163456Z","title":"Multi-armed bandit problems with history","venue":null,"work_id":"5b2f3513-0a28-4eca-83a3-cc94de2d6688","year":2012},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.422108Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:4592b6fdfe1833962e7bf883ebaaaad8fd8fbe0a3bc52a6b248df67401f26379","observation_id":"247d80e5-6473-4f31-b5dd-f829a1170211","resolution":{"observed_at":"2026-08-06T20:33:22.167493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.149460Z","title":"Bayesian decision-making under misspecified priors with applications to meta-learning","venue":null,"work_id":"c5117f10-3011-4fb7-a3c8-f6af1d4a110c","year":2021},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.465561Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:7c9d15c2288cd887711907b882df92e5fb642b2083f6defeb10fd35a0deaac3e","observation_id":"5e5ccfef-53eb-4b73-ba67-8ff715eb44b6","resolution":{"observed_at":"2026-08-06T20:33:22.153748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.135324Z","title":"An introduction to matrix concentration inequalities","venue":null,"work_id":"873acd57-da09-4038-b1e2-183da79633ba","year":2015},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.534771Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:21e62524d94ce3b2fdcee8a769b0701327cf20e3a4e35e346c770508eb6b7e9d","observation_id":"983dce12-809f-477d-9f96-60d4cf2279df","resolution":{"observed_at":"2026-08-06T20:33:22.140229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1011.3027","last_updated":"2011-11-23T21:11:38Z","snapshot_observed_at":"2026-08-04T12:57:10.755670Z","submitted_at":"2010-11-12T20:20:28Z","title":"Introduction to the non-asymptotic analysis of random matrices","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1011.3027","snapshot_observed_at":"2026-08-06T20:33:16.599044Z","title":"Introduction to the non-asymptotic analysis of random matrices","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.599044Z"},"links":{"cited_paper":"/paper/1011.3027","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:16acaf9a880a4d4a776ee78b728c19110a406918651b5917f90b3e14be9c015d","observation_id":"a44f6b3a-7ff8-4656-a54e-f90523b8ece6","resolution":{"observed_at":"2026-08-06T20:33:16.599044Z","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":"2026-08-06T20:33:22.121563Z","title":"Leveraging offline data in online reinforcement learning","venue":null,"work_id":"d68fa8a5-c35f-43a3-856a-0719aa774ec0","year":2023},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.686754Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:6991c6b1fa9de0de0f3d76ca6637c686df7067196daa25a997ff672c49c1d774","observation_id":"ee013ed9-937d-4301-995c-00566c1fd294","resolution":{"observed_at":"2026-08-06T20:33:22.126393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.107425Z","title":"Taking a hint: How to leverage loss predictors in contextual bandits? In Conference on Learning Theory, pages 3583–3634","venue":null,"work_id":"e644803d-c783-4c19-806b-6647aa53a9bb","year":2020},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.753176Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:a495e5712559b804000b16dd8b251cbb4a1205988786c300bebe007c9b3d056e","observation_id":"6e9ed2e4-4075-463e-a40d-0761bd32fad4","resolution":{"observed_at":"2026-08-06T20:33:22.112092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.05699","last_updated":"2020-11-07T13:27:07Z","snapshot_observed_at":"2026-08-08T17:34:09.413301Z","submitted_at":"2020-01-16T08:58:42Z","title":"Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision","version":2},"cited_work":{"arxiv_id":"2001.05699","doi":null,"metadata_source":"pith","pith_arxiv_id":"2001.05699","snapshot_observed_at":"2026-08-06T20:33:18.131333Z","title":"Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision","venue":"cs.LG","work_id":"9fc76610-a929-4958-bcb1-0dc10104c3e1","year":2020},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.805533Z"},"links":{"cited_paper":"/paper/2001.05699","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:8b4093acc8ac1f017bf4eb11b8cda95a1376a85154e74f4926216a787d472c65","observation_id":"4b0e3928-b3fa-4c48-96a9-ba8d15893896","resolution":{"observed_at":"2026-08-06T20:33:18.238480Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.093551Z","title":"Advancements in Management Science: Applications to Online Retail, Healthcare, and Non-Profit Fundraising","venue":null,"work_id":"200bad02-6a2a-4615-850c-ef70cf20238d","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.872320Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:8e536ecfcdf472ce58eaba7306727bff7a904bf1c17a7f583335afa25c918f9a","observation_id":"06c12b4b-f294-486e-8eb1-8b9c08d18368","resolution":{"observed_at":"2026-08-06T20:33:22.097895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.00301","last_updated":"2019-06-21T19:25:56Z","snapshot_observed_at":"2026-07-06T07:24:28.731159Z","submitted_at":"2019-01-02T09:15:02Z","title":"Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.00301","snapshot_observed_at":"2026-08-06T20:33:16.976339Z","title":"Warm-starting contextual bandits: Robustly combining supervised and bandit feedback","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.976339Z"},"links":{"cited_paper":"/paper/1901.00301","citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:14661b771833e4e5ea0d9a79d4b3258ac4301d9506642da489da3d7c5aa7a5f8","observation_id":"e2f5db4e-ce7f-4cb1-8233-c99ba55cd10e","resolution":{"observed_at":"2026-08-06T20:33:16.976339Z","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":"2026-08-06T20:33:21.789796Z","title":"t−1X s=1 ∆α⊤ t x 2 # − Ex,y","venue":null,"work_id":"ca96dd03-72fe-4d3d-bd88-0ae7819d2242","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.038217Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:59538e0b0d8e30f7eb544057ae3c5486112a1b23ef0ec7cbb07ee74811db3ece","observation_id":"fecf07e8-2462-4764-82f6-77c5286b6818","resolution":{"observed_at":"2026-08-06T20:33:21.869808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:21.580186Z","title":null,"venue":null,"work_id":"2807808f-53ca-4ba5-aa5d-6a5447854a60","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.097820Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:54861405d89ffedcbf5f0cb1448d83507c7aca617f1290c2d3c2e513757f3aaf","observation_id":"987c1596-65c6-43f2-8273-f6cc5f61917d","resolution":{"observed_at":"2026-08-06T20:33:21.694631Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:21.280830Z","title":"Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper","venue":null,"work_id":"901eafc7-fd34-4965-9acd-f2b5c37b803e","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.180742Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:fe2e81271622e7ab06b322f0996dfe065919f0c94beaa3dc6c29abcce9efdbcb","observation_id":"aebda9a1-9bf8-43a4-b61b-a72721199f98","resolution":{"observed_at":"2026-08-06T20:33:21.421065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:21.088031Z","title":"Limitations","venue":null,"work_id":"3973a6b2-b4ca-410a-9245-1074caccba58","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.214653Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:ee4c4d3061e77c8f1ff4cb0c4d410719b9dcc568761f4105ca0ee006f9615b6f","observation_id":"b90932e0-ee83-4562-8448-c73fecf37b72","resolution":{"observed_at":"2026-08-06T20:33:21.159930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.804946Z","title":"Guidelines: • The answer NA means that the paper does not include theoretical results","venue":null,"work_id":"bc22c6c1-a9b0-45f3-bfdd-622c31d4ed7c","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.260237Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:a817e50d0fc878325fb9c81e2395340ce6069ec9d48052d8699f481e75f5d969","observation_id":"97f68b6a-9ad6-442c-932d-9cf00686b692","resolution":{"observed_at":"2026-08-06T20:33:20.919276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.684718Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"518376a4-311e-42d5-9b8f-61e57f82a9d4","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.309575Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:d06dd6df3a5005b99b6293047b70bb10b116e5b585cbacef1b49a97c874921f0","observation_id":"af5a1175-e007-4413-8f72-880c28eca7a6","resolution":{"observed_at":"2026-08-06T20:33:20.749200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.560820Z","title":"Guidelines: • The answer NA means that paper does not include experiments requiring code","venue":null,"work_id":"3a3c12b9-559e-4d6c-badd-d27836e4a0fa","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.376451Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:e3e8f12b6fd46080710b447f855393272f7d712aff538bed85f4b4ff35915a80","observation_id":"9088a5ef-0437-4e1f-801f-54d6a92d6f42","resolution":{"observed_at":"2026-08-06T20:33:20.623305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.414366Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"32f93e77-097b-4b01-a7ec-bd99600f5179","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.441365Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:831d7451d90dc45822ebeff4aebf3c816e70a5dc484333f6a7a3a0b0c9aab2a1","observation_id":"b39d4938-92b0-4ed5-ac63-01cd2ff01698","resolution":{"observed_at":"2026-08-06T20:33:20.475252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.218764Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"4717fd2d-bea2-4189-9c42-165734316434","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.499767Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:88a778929d60d6f1236fc43e39c3f4e65ce3b3a7e99f7d5b7a4b54ed306b050c","observation_id":"a95dfe66-d81c-4601-b88b-598c32f69597","resolution":{"observed_at":"2026-08-06T20:33:20.282423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:20.107916Z","title":"All experiments can be conducted on a personal computer","venue":null,"work_id":"c1f748d7-aa4b-4d21-a943-7cbb55f88521","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.563665Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:e4dea326e56f9343f7b1607f68ee151bfde6bb0583064548d1b719a5811dff6f","observation_id":"9c240bdf-14d7-42e2-beb9-90c37861992d","resolution":{"observed_at":"2026-08-06T20:33:20.153291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.968800Z","title":"Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics","venue":null,"work_id":"2df34e0c-c6b8-4f9e-a97e-8ea762be1242","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.640930Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:3e8032a4ce25b3cefa01c83c4e45b061e1c2ebf1b13f768e864bede58da664a1","observation_id":"2a9b71df-8485-41c3-bbdf-b0c25fab5b7d","resolution":{"observed_at":"2026-08-06T20:33:20.038850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.820087Z","title":"Guidelines: • The answer NA means that there is no societal impact of the work performed","venue":null,"work_id":"537cdb40-7fc6-4cda-ab1b-72cf04c78a7e","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.697797Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:a450f2849601ac579fc9e187ee698d2f27563d864d6715fce5e868d0a4fa88ec","observation_id":"19c2b4ab-3ea1-4d80-beaf-235882d7c178","resolution":{"observed_at":"2026-08-06T20:33:19.911154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.663217Z","title":"Guidelines: • The answer NA means that the paper poses no such risks","venue":null,"work_id":"05dc1900-ae1e-47e3-bc44-6226086f5e94","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.758623Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:926d867f4c0ed6bb89dcf057fb36b62649c9652b69a7e895650d2d7c7eb44d81","observation_id":"abd258c7-8120-43ec-a223-ec67ffb49945","resolution":{"observed_at":"2026-08-06T20:33:19.711561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.523442Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"22f3f6ff-9932-4e32-8578-93a74f1b7d59","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.799712Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:2dff5aa74eaff0a28489273c31de4c4fd1f0fcfe6e3577ffa48560d80f245173","observation_id":"50d06174-945b-424a-ab9f-9579cd07eda2","resolution":{"observed_at":"2026-08-06T20:33:19.616723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.429387Z","title":"Guidelines: • The answer NA means that the paper does not release new assets","venue":null,"work_id":"febe0972-1560-49ab-b608-e25e217650bf","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.864397Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:7dd23590b5c19588ae37847adc6ae68c60f7d6db437945efe39f522c44734e1a","observation_id":"90d748e5-ce67-41e5-b1be-7d2d2e7c123a","resolution":{"observed_at":"2026-08-06T20:33:19.469450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:17.925171Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.925171Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:f5dca2cb9d4b5e1226a469bac842a1bf291df2036cfdd08e1160f61989edbccf","observation_id":"a0b7bb91-dd4a-4ef1-afcc-c4b2f8ce2853","resolution":{"observed_at":"2026-08-06T20:33:17.925171Z","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":"2026-08-06T20:33:19.303196Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":"8ce54685-6d60-4a7f-b196-98aea5af02c9","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:17.976877Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:bd5832d34336d4bd0c4dbe3d5178f515ac1ba7137775d7191a7f83795c32fced","observation_id":"b65e9f0a-9100-4aee-addc-f813d061a6d9","resolution":{"observed_at":"2026-08-06T20:33:19.344744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:19.102256Z","title":"Answer: [NA] Justification: The core method development in this research does not involve LLMs as any important, original, or non-standard components","venue":null,"work_id":"41b825a7-5525-4e02-9c89-4de8a234958d","year":2025},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:18.029095Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:d27d903430cf854cdc4c11a3330d6513da005be3edc638983ebb45c722609e92","observation_id":"e9ee8387-9b5f-4590-bb48-0880f63faa30","resolution":{"observed_at":"2026-08-06T20:33:19.210117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.344760Z","title":null,"venue":null,"work_id":"6146a313-dea5-487b-8a6a-6ec23d17a11a","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:14.521979Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:26b58fca74ae44cb0cfce0ceee8654ad78ea832a502a5cd0f9ec0b1f4d065d4d","observation_id":"e7986b3b-34d7-4a53-9d71-2c6105eb5cfb","resolution":{"observed_at":"2026-08-06T20:33:22.349047Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T20:33:22.034548Z","title":null,"venue":null,"work_id":"5e8aadf4-e971-42ca-88fb-be6584745e4f","year":null},"citing_paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:16.918124Z"},"links":{"citing_paper":"/paper/2507.02762"},"observation_digest":"sha256:6e0519d07f693d2ce9b78dfde80c2bc4cff436f0134c846651e6f7fed0f4af67","observation_id":"e8607e64-44f3-43cc-b21b-1b6702e5cf79","resolution":{"observed_at":"2026-08-06T20:33:22.083542Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.02762","last_updated":"2025-07-03T16:21:49Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T23:42:20.121235Z","submitted_at":"2025-07-03T16:21:49Z","title":"Contextual Online Pricing with (Biased) Offline Data"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":9,"verified_exact":3,"verified_fuzzy":36},"total_outbound_references":49},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2507.02762."}