{"as_of":"2026-08-09T11:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8f61cd47c20a4c78b9089ed06ba1edd1877ee0b88c8e92000c9e13118b1097bd","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:07:06.268923Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2506.03802/citation-record","integrity":"/paper/2506.03802/integrity","json":"/paper/2506.03802/citation-record.json","paper":"/paper/2506.03802"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:07:07.631007Z","title":"Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games","venue":null,"work_id":"78edad30-2dea-400a-98ab-0eaf7b7baf2f","year":2022},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.357726Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:600695809fa3668d61a4bba1d9dc67d28012354b0254a484303f5edf3d58ab1a","observation_id":"6ed534b5-dddd-4707-879c-d0f5c6ca3a92","resolution":{"observed_at":"2026-08-07T11:07:07.634563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.617020Z","title":"Uncoupled learning dynamics with o(\\log t) swap regret in multiplayer games","venue":null,"work_id":"2b28fad0-66f2-4ad8-bed3-e649f5f2c6ef","year":2022},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.403509Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:b93a3be643b63879e6f2f335b7cf2e01b73b374417b1c11dcf1e5f4f7e2bad33","observation_id":"e0c1f95f-e6e9-4d8e-9afa-e46a660aaa74","resolution":{"observed_at":"2026-08-07T11:07:07.620260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03018","last_updated":"2025-01-06T13:59:57Z","snapshot_observed_at":"2026-07-06T20:17:06.835639Z","submitted_at":"2025-01-06T13:59:57Z","title":"Probably Correct Optimal Stable Matching for Two-Sided Markets Under Uncertainty","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03018","snapshot_observed_at":"2026-08-07T11:07:01.454603Z","title":"Probably correct op- timal stable matching for two-sided markets under uncertainty.arXiv preprint arXiv:2501.03018, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.454603Z"},"links":{"cited_paper":"/paper/2501.03018","citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:fb09d33662e0b1c1775560fde259dc37ba94d16666b14ac0bc0600660a11716c","observation_id":"cbad86d3-1cdc-4308-941c-80dc8a179505","resolution":{"observed_at":"2026-08-07T11:07:01.454603Z","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":"2026-08-07T11:07:07.607296Z","title":"Gambling in a rigged casino: The adversarial multi-armed bandit problem","venue":null,"work_id":"9caf2520-7256-4828-85a6-3b6a4d79d4a4","year":1995},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.517840Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:46a7143ea0a1d90aa22ce982b405a58d2ceacf0c062b9466b9781b6815321fdc","observation_id":"c6e4132c-a56f-47b3-98a0-44b5bfbc5d80","resolution":{"observed_at":"2026-08-07T11:07:07.610710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.597590Z","title":"The cost of stability in coalitional games","venue":null,"work_id":"65e29773-f830-434e-a13a-8bccadffa8c5","year":2009},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.588282Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:0c1a21ff15a7bc4ffd09b48556cb8b2d8a582dd26b23456a9c4e671b9c8e0b54","observation_id":"8b711f67-65e2-463f-b003-b41eaa0f8449","resolution":{"observed_at":"2026-08-07T11:07:07.600772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.570934Z","title":"Beyond log2(t) regret for decentralized bandits in matching markets","venue":null,"work_id":"4b21c539-af2c-4825-8e2a-fcb9426f1b8b","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.726675Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:b1425d8c4e83abf6a2d9d38f87e52c4401f0aa91a0b94f2069a8c3f5079cd537","observation_id":"1510f41b-93f0-4475-a974-a7750ca368c3","resolution":{"observed_at":"2026-08-07T11:07:07.576102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.558265Z","title":"Zero-sum polymatrix games: A generalization of minmax","venue":null,"work_id":"41974a00-1639-4bd0-bf95-874bd63a0831","year":2016},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.791861Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:112ff6e3041a582e95454cc175d23a1fbc2120dbc0d82fcbf295ca000d88d99b","observation_id":"3bbdd5d1-a7c9-447e-bbe0-3327c123d0f0","resolution":{"observed_at":"2026-08-07T11:07:07.562264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.543806Z","title":"Competing against Nash equilibria in adversarially changing zero-sum games","venue":null,"work_id":"b58ef9c5-dee6-4b34-8cd1-e874f8620ab1","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.861459Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:e85d4a9dab0382094913f62049f65c6c43e0dad5a06efccc9abca0e6ed9efa10","observation_id":"eb99278e-aff0-4298-b433-9b6882627f6c","resolution":{"observed_at":"2026-08-07T11:07:07.547559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.514774Z","title":"Cen and Devavrat Shah","venue":null,"work_id":"607dbf9d-856f-4d94-8f09-42d48fffe54f","year":2022},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.983672Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:44d4c7092125ced2ff5c80bcc1c941896f354f8f9a7506b05650a9e9f63db1eb","observation_id":"2a171a29-0608-44b4-bd84-87cc89bba386","resolution":{"observed_at":"2026-08-07T11:07:07.517878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.505193Z","title":"Prediction, Learning, and Games","venue":null,"work_id":"3d8b564e-e8ee-4489-9ec9-06a0246e1d91","year":2006},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.044652Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:62b1434d19da350cb2a9d4d9902fdd3dbf2512617ca06fb6ae544a645d58295f","observation_id":"9490cf7f-9c0e-477b-b404-5b4d1e29c776","resolution":{"observed_at":"2026-08-07T11:07:07.508355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.494617Z","title":"Hedging in games: Faster convergence of external and swap regrets","venue":null,"work_id":"e3270023-b44f-4d40-8df8-e5c7b3a39829","year":2020},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.107160Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:b0b8f92db66e4138faabcf220b6dca049cb8d12f599fdce68239a969db07fdec","observation_id":"119763ac-9d62-434c-a3d6-f268b5c7b40f","resolution":{"observed_at":"2026-08-07T11:07:07.497928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.484961Z","title":"Two-sided bandits and the dating market","venue":null,"work_id":"551855a0-34f3-4937-b18c-1f0319699a9f","year":2005},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.167390Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:6d573141dd3bef9b1d9ebfdf97e3591248fd305d901accfbb8a458f3420cecfa","observation_id":"b2790c61-e486-483f-bba9-60b3f7e077cd","resolution":{"observed_at":"2026-08-07T11:07:07.488168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.474234Z","title":"Near-optimal no-regret algo- rithms for zero-sum games","venue":null,"work_id":"671d1ecd-b934-4fc1-819f-76ed7100a67d","year":2011},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.222472Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:f4aa15295bbc0cffd3b21b459d134c5def1d2ea0592e93b316af3d01951b180e","observation_id":"98c64243-d2ee-47d2-92a9-19e63eddacf4","resolution":{"observed_at":"2026-08-07T11:07:07.478069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.463375Z","title":"Near-optimal no-regret learning in general games","venue":null,"work_id":"66b15357-b495-4a3d-bcca-d857f37362ee","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.290350Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:cefef21f91c738edb8da8793e93d31f5520679b95505dad747a465c8c8b524e2","observation_id":"eaa410db-9b1d-45d8-8f29-655f2333d282","resolution":{"observed_at":"2026-08-07T11:07:07.466886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.451857Z","title":"Near-optimal no-regret learning dynamics for general convex games","venue":null,"work_id":"5bee5df9-aaa6-4c04-8982-97182ba38373","year":2022},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.361605Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:44dfcb061727691f75fd2193b14cea795a936dd945957004fbc38fe880fec1f0","observation_id":"064af466-a9e2-4855-91e2-cb6fc4e87f8b","resolution":{"observed_at":"2026-08-07T11:07:07.455507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.440757Z","title":"Asymptotic calibration.Biometrika, 85(2):379–390, 1998","venue":null,"work_id":"e9e79098-99bd-4876-8873-f2931f254d03","year":1998},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.427372Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:6eeacc8cff8f00782051d6140d15e6fe5fc288a2c65dda7eaeba1c123b60bc33","observation_id":"0f8c2c0d-dbf1-4679-8d80-5c1f1a2e5203","resolution":{"observed_at":"2026-08-07T11:07:07.444671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:02.506193Z","title":"Gale and L","venue":null,"work_id":null,"year":1962},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.506193Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:99501aaaa15f43ef35af74520a2a616cdd24457aaf8f3a18ca01bd5812b29a14","observation_id":"9b1c0316-f318-4065-b019-1388858b6233","resolution":{"observed_at":"2026-08-07T11:07:02.506193Z","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":"10.1007/s00182-009-0218-x","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:03:45.533247Z","title":"Decentralized job matching","venue":"International Journal of Game Theory","work_id":"afcca080-3b66-4465-98d6-21cc462e091a","year":2011},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.598588Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:5e2e1d6c1966e2dac9f80ac5c949061349305888ad477c2567b6225f761f56ab","observation_id":"c3704cd9-c1c3-4055-b0bb-4643ec9909e0","resolution":{"observed_at":"2026-08-07T11:07:06.718964Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.428703Z","title":"Approximation to bayes risk in repeated play","venue":null,"work_id":"b73309b4-cc3e-4eb2-ac0f-68b554872997","year":1957},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.668356Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:824802abfec10b2ddfa3370408c6d1476417262609070658650fccbb37332d8f","observation_id":"86c46f27-8064-439d-979c-48ebb1e995b6","resolution":{"observed_at":"2026-08-07T11:07:07.432511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.416338Z","title":"A simple adaptive procedure leading to correlated equilib- rium","venue":null,"work_id":"d36106bd-1ea1-4a30-9fa1-205615d493ea","year":2000},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.762219Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:30c8372fb2e49ca6f276190fefbd2038c34e63cd24667e3bb4ae2345719f2c33","observation_id":"dfc261e9-8699-4ee4-a6ff-9c5e3558979b","resolution":{"observed_at":"2026-08-07T11:07:07.421161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.403428Z","title":"Putting gale & shapley to work: Guaranteeing stability through learning","venue":null,"work_id":"57929aa2-a6a9-4b28-ab8e-918dad32cd30","year":2024},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.852446Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:844187a441d02f2128d528c08a053d4507a487cf5982273db26576153634574d","observation_id":"e27aa60b-1ebc-4106-8820-e183cc61ad6c","resolution":{"observed_at":"2026-08-07T11:07:07.406905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.17625","last_updated":"2025-02-24T20:20:06Z","snapshot_observed_at":"2026-08-07T17:51:59.763334Z","submitted_at":"2025-02-24T20:20:06Z","title":"Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback","version":1},"cited_work":{"arxiv_id":"2502.17625","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.17625","snapshot_observed_at":"2026-08-07T11:07:06.976028Z","title":"Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback","venue":"cs.LG","work_id":"199858cd-1525-4940-9f0c-3e4be96fe689","year":2025},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:02.905677Z"},"links":{"cited_paper":"/paper/2502.17625","citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:db0df16b646b0ebca04ef1496daa6daeed7ccac22fca9b8adcbfc99459c01660","observation_id":"8aa4244a-7f95-4fe3-8a00-0c655f4cc1ea","resolution":{"observed_at":"2026-08-07T11:07:06.980695Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.392389Z","title":"Equilibrium existence in bipartite social games: A generalization of stable matchings","venue":null,"work_id":"c9826c6f-ac47-41a0-a4f8-c6909c0fc010","year":2008},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.028139Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:02019bec155d208c1d16e8428f9bce6de4c84a69172074f4f98bc1c4493d14dd","observation_id":"20703b43-300b-4bf5-9460-e74a7bb98901","resolution":{"observed_at":"2026-08-07T11:07:07.396155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.380323Z","title":"Social games: Matching and the play of finitely repeated games","venue":null,"work_id":"6f9172ea-fd87-423a-adc4-ce4537e3d190","year":2010},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.160110Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:79ee96aadc9857ec0f61bcff249341c588852afc1f2f6350266f4904814f7e71","observation_id":"f4cddc13-c817-42de-9949-1570d4cf39da","resolution":{"observed_at":"2026-08-07T11:07:07.384368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.369530Z","title":"Learn- ing equilibria in matching markets from bandit feedback","venue":null,"work_id":"a5d4d5ac-5eca-46b2-b08c-e07617d941a8","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.285191Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:b7146073b01bfd24f7460d04de2f4f191bf25ef455dff94801494c5d6f9f8d77","observation_id":"3363e17c-4bc6-4763-9e86-5353b831d76c","resolution":{"observed_at":"2026-08-07T11:07:07.373240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.08843","last_updated":"2023-01-31T22:35:43Z","snapshot_observed_at":"2026-07-06T11:39:44.670619Z","submitted_at":"2021-08-19T17:59:28Z","title":"Learning Equilibria in Matching Markets from Bandit Feedback","version":2},"cited_work":{"arxiv_id":"2108.08843","doi":null,"metadata_source":"pith","pith_arxiv_id":"2108.08843","snapshot_observed_at":"2026-08-07T11:07:06.956690Z","title":"Learning Equilibria in Matching Markets from Bandit Feedback","venue":"cs.LG","work_id":"381f4cfc-eb19-4c73-993c-2340106fc2fe","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.405976Z"},"links":{"cited_paper":"/paper/2108.08843","citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:868e943e3a8e82efc61f8e0be9e2971f9831b4b14a8ef84c101a92da5a91ffdc","observation_id":"2504b3d0-d8b6-4862-9f5a-1f6e6f64bcab","resolution":{"observed_at":"2026-08-07T11:07:06.961736Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:03.496343Z","title":"Thompson sampling for bandit learning in matching markets","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.496343Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:e310517d1983fd0f6fa0993d63685ae121186595042e44e01b94dbdcef7fbd8a","observation_id":"1ec2cd0a-9847-43b0-80bc-548de0d8df2c","resolution":{"observed_at":"2026-08-07T11:07:03.496343Z","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":"2026-08-07T11:07:07.359000Z","title":"Bandit algorithms","venue":null,"work_id":"d2478c59-d62e-4c9e-9440-afca045f9ee7","year":2017},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.597425Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:219b32eacb6a08e11214d532aaa4c5f751590ddc235f712809d6881c3ad721fa","observation_id":"6dbba708-aaf1-4f75-a9b4-8467e1751a91","resolution":{"observed_at":"2026-08-07T11:07:07.362246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:03.670479Z","title":"The weighted majority algorithm","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.670479Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:65e8ecf7d23715bf861aef08914cfd5a38a8e2cb99269d958b4af2a3b403ccce","observation_id":"749a65e6-d623-46ac-9399-dd2ba71ca6e2","resolution":{"observed_at":"2026-08-07T11:07:03.670479Z","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":"2026-08-07T11:07:07.339198Z","title":"Liu, Horia Mania, and Michael Jordan","venue":null,"work_id":"e5f388c6-9761-4977-bbb2-d8c255931e63","year":2020},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.796881Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:bc982b7948cd4bc9f43eb281afde06ff8d60962c8bdc426fbeb1bad7731757fe","observation_id":"ccb2466b-72a8-450d-a182-1bbebf4a87cb","resolution":{"observed_at":"2026-08-07T11:07:07.344342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.324729Z","title":"Bandit learning in decentralized matching markets","venue":null,"work_id":"b07914cf-cc73-4c5e-bf7f-76f619675188","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:03.920168Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:726cfc0c4f3cfe14838ff03ee834da92e5ee4a83b1fdf1543a5ff9a696abe8e7","observation_id":"c1210ba0-7425-4673-a814-c01d0745581b","resolution":{"observed_at":"2026-08-07T11:07:07.330033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.311694Z","title":"Instance-dependent sample complexity bounds for zero-sum matrix games","venue":null,"work_id":"6c72c9b3-6bf0-49c2-839b-3aae5d29ada6","year":2023},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.027734Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:cc63aa31a04c66022af3c038cc0920cf97d166180a988c9c967a98858cd01b9b","observation_id":"71711ff0-59d1-4553-a3ea-ce4cdd2cb807","resolution":{"observed_at":"2026-08-07T11:07:07.315767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.298913Z","title":"Compet- ing bandits in time varying matching markets","venue":null,"work_id":"347598d0-d5ec-466b-a9b7-1e051b0480b7","year":2023},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.147692Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:44b25eec73114454d9be70d5c77b4a0ceedc3a9f8835e88b98de4f259678b4d0","observation_id":"7427cacc-8ffa-4762-bdec-9be768a83500","resolution":{"observed_at":"2026-08-07T11:07:07.303019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.280282Z","title":"Non-cooperative games","venue":null,"work_id":"54b278ec-92eb-482f-8de0-b8c1fdb8fa03","year":2024},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.239247Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:2823f07a70a6a1acae73b795a79c3d804ebde948dd4f0517a998b22eee82563f","observation_id":"45b60d79-dcfb-473d-a7e3-b1126a5676de","resolution":{"observed_at":"2026-08-07T11:07:07.284680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.267651Z","title":"Vazirani.Algorithmic Game Theory","venue":null,"work_id":"7153249c-6b00-4e30-ac2f-e950f1af2228","year":2007},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.342811Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:20fa59b5903d93b45584c0b5c2910b9def2dbceed004eec425b047e07f359419","observation_id":"402e102f-ae6f-448f-b9c3-46d09a8317b4","resolution":{"observed_at":"2026-08-07T11:07:07.271624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.252812Z","title":"Matrix games with bandit feedback","venue":null,"work_id":"9653b995-89e5-46b8-9281-101acc380827","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.460402Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:62cfaa53b0fb98c61494b2c5360e157e2185bfd1f596a6e9ab2f6e6e86ef2b1c","observation_id":"b404fcfb-7cb6-4c5c-a8e2-131ef3fbf66f","resolution":{"observed_at":"2026-08-07T11:07:07.257450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.239633Z","title":"Optimization, learning, and games with predictable sequences","venue":null,"work_id":"dabf0fa8-a3ad-4981-ae1f-bb6bf76cac97","year":2013},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.641455Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:7812acbc40d096e8d27ff55dfe95c6102ce050878982adcfa63f42cda50f89e2","observation_id":"6549090c-cb71-4f8c-a03b-6aad636f4f53","resolution":{"observed_at":"2026-08-07T11:07:07.245027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.228524Z","title":"An iterative method of solving a game","venue":null,"work_id":"4ba65549-6cab-4593-a991-e7585b9e21fd","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.733232Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:f22bbba8df0890f53b2a2300acb881572fd44c33b072ff316e17126986603a44","observation_id":"075845c9-7d72-4e50-8728-fbdc1366ae5e","resolution":{"observed_at":"2026-08-07T11:07:07.232080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.216329Z","title":"The evolution of the labor market for medical interns and residents: a case study in game theory","venue":null,"work_id":"f243baab-4fd5-4171-9bea-05e5f6ddd7a9","year":1984},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.992881Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:78d96027b2d3b5dce7d55616701f16df339e1a359ef3d408741857dbc1165c9b","observation_id":"8d37ef4b-89ec-4c17-bcc5-76e6a7e9d66b","resolution":{"observed_at":"2026-08-07T11:07:07.220126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.205585Z","title":"Roth and Marilda A","venue":null,"work_id":"4bf2e3e1-4ab0-47b0-902f-c67eccc89c7f","year":1990},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.098687Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:76bab921592d8096ae6501b0a798fcda8515694a81bc4075143328f19ec60660","observation_id":"a867c3f3-ad3f-4c80-851d-dc387f7a0029","resolution":{"observed_at":"2026-08-07T11:07:07.208853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.194056Z","title":"Dominate or delete: Decentralized competing bandits in serial dictatorship","venue":null,"work_id":"9a39fe69-e673-4fb4-9321-333fb1383dc1","year":2021},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.221608Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:73d2307770bc6bab56c77d964b7f4d1167db26ef5b3c13445b665b6c06146c72","observation_id":"7502628f-174c-4911-9314-e1fc7811c63d","resolution":{"observed_at":"2026-08-07T11:07:07.197936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.183372Z","title":"Quasi-cores in a monetary economy with nonconvex preferences","venue":null,"work_id":"ce6399f7-9264-48d4-ad02-f1b05c34c03d","year":1966},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.322325Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:04c40d468b71eee9c0d8403378f27ec2d1b34ac20aa99ac19e189b2b295ad8be","observation_id":"7318b154-937a-4360-beba-b8ce34bd520e","resolution":{"observed_at":"2026-08-07T11:07:07.187089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:05.397588Z","title":"Fast convergence of regularized learning in games","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.397588Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:7ac2292580852d2cc072c5b2eaf6bc19504d4af73b27686b3501abf06d858780","observation_id":"972e5027-23b5-4ddc-a150-9a71acd110f7","resolution":{"observed_at":"2026-08-07T11:07:05.397588Z","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":"2026-08-07T11:07:07.164541Z","title":null,"venue":null,"work_id":"5c15f494-0b85-403d-9ad9-ab54445a443e","year":1928},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.476851Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:bef5028a90dbf3956d856e3ac3758afa4ededf0cbeef5c6d3b12a612a46a4ed9","observation_id":"35eaf28a-5117-48a2-bac2-91bd87ad986c","resolution":{"observed_at":"2026-08-07T11:07:07.167713Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.154127Z","title":"Morgenstern, 0","venue":null,"work_id":"0f875ab5-8036-4b11-a8ab-de42f788afd2","year":1944},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.582159Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:fa22c5c7670e53a766d904589632578304c3e91c6903b7c73ca7cd9d8fd1f8b8","observation_id":"14c47075-84a2-4cbb-ab8c-c93405fa8e71","resolution":{"observed_at":"2026-08-07T11:07:07.157569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.143457Z","title":"More adaptive algorithms for adversarial bandits","venue":null,"work_id":"e45ebd90-1de6-470f-98f0-8bc9c0dac65a","year":2018},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.669146Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:ab5c0859fc4af28a7457f59c8a6edf03da31e341ec49eaf61159c9f527375db4","observation_id":"f88d8e2b-23ec-481c-b292-db16fb3cc021","resolution":{"observed_at":"2026-08-07T11:07:07.146911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.131107Z","title":null,"venue":null,"work_id":"74cf25ce-7fcf-4e60-ae82-03fe6e0d9246","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.758183Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:e6aec4d285cf3e94e5f900a9964aeb4725f5514f57998bf2f4d57ed919741765","observation_id":"b5d03f9c-a95d-442e-b404-fd636b081af6","resolution":{"observed_at":"2026-08-07T11:07:07.134646Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.117401Z","title":"B) The matching m is stable under the strategies X","venue":null,"work_id":"5c4fc9a1-a455-4c2c-b8b6-15f3219e9585","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.837667Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:35c857d76bb4632937fb6acac01601bb3a5109bf63bbe4f91ccdc747f4897a6f","observation_id":"2b7a4494-0d64-4bbd-be87-a4dfbc417bc0","resolution":{"observed_at":"2026-08-07T11:07:07.121333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.105805Z","title":null,"venue":null,"work_id":"1179fa6a-60cb-41d7-931b-38ff933f226d","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:05.916899Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:557ebbd4b03d1da72dea4beb7213aba5df272825671a06d114661e035939189e","observation_id":"bfc95cea-f11b-4e7d-90bd-2472ae86aa21","resolution":{"observed_at":"2026-08-07T11:07:07.109407Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.095090Z","title":null,"venue":null,"work_id":"0b678efa-94ba-4728-8338-999a575ad0f3","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:06.051084Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:e9ec0364cf407778d15356a07df87d5bc39f1d69fb6471e169e03d02e083a4aa","observation_id":"35c631c2-8be0-4efb-a2ea-2df0b4954f51","resolution":{"observed_at":"2026-08-07T11:07:07.098396Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.082220Z","title":"We denote by (x⋆ p, y⋆ a) the Nash equilibrium of the game with payoff matrix ¯Ap,a, and by ¯V ⋆ p,a = x⋆T p ¯Ap,ay⋆ a the value of the game","venue":null,"work_id":"df895992-4d0f-451c-8acf-befacbd409ad","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:06.184192Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:877a1c8c9399da38ebc1272b60199e43846a74123b1a18f3f4e2b702e8fa8456","observation_id":"d0572fe9-866d-45ed-9d97-b2b44c798d0b","resolution":{"observed_at":"2026-08-07T11:07:07.086422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.069995Z","title":"s 2 1 ∨ nt a,mt(a)(ita, it mt(a)) log 1 δ # (31) ≤ 2 TX t=1 X (p,a)∈mt E","venue":null,"work_id":"efc8ff6f-3bef-4c7c-ba6a-731b1bb94197","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:06.268923Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:7c00190c1b77d1a5afbce25f19c2c8fa15d3ada1c2ad9122038f6a94c361a693","observation_id":"e731f173-e8c1-42b0-adaf-b1ffb690c541","resolution":{"observed_at":"2026-08-07T11:07:07.074288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"stable/1969530","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:07:06.939411Z","title":"URL http://www.jstor.org/stable/1969530","venue":null,"work_id":"3b0afc5b-18c7-4e7f-87dd-518bd17a1318","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":1951,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:04.853480Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:d48bc5bdb95631e669ed0f522af5647cca10351f780f549bdbbe5563d5cf9974","observation_id":"a09aaf13-bfb2-4037-ae96-cecc71722f49","resolution":{"observed_at":"2026-08-07T11:07:06.945369Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.585911Z","title":"Springer, 2009","venue":null,"work_id":"8be15fe2-dd6c-4189-a70c-9fe4c900170b","year":2009},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.653792Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:84f771f96b2f81c11bf589aebe1868ee9a0d473e02139c226cb2af451173fe64","observation_id":"1eb2cdfe-f3f8-4cd2-b860-cc6107804387","resolution":{"observed_at":"2026-08-07T11:07:07.590135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:07:07.525160Z","title":null,"venue":null,"work_id":"d0b6ccd6-6d2d-4b09-bef6-3c79c0c4e25f","year":null},"citing_paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T11:07:01.925779Z"},"links":{"citing_paper":"/paper/2506.03802"},"observation_digest":"sha256:838e9e65de56d8dff3f76ace3e8b952c52a81f1dbc0f721913eefb5f160e8b44","observation_id":"28f78664-470c-486a-a09a-4f0bf3f3c660","resolution":{"observed_at":"2026-08-07T11:07:07.529162Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.03802","last_updated":"2026-06-16T13:36:16Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T10:52:41.892791Z","submitted_at":"2025-06-04T10:15:51Z","title":"Learning in Matching Games with Bandit Feedback"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":10,"verified_exact":3,"verified_fuzzy":41},"total_outbound_references":55},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2506.03802."}