{"as_of":"2026-08-15T21:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7411ddff54df84fbf2b06e88ee25fce8fd3142bded108b92b106bfdd12a20fcb","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:59:45.532689Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/2505.17365/citation-record","integrity":"/paper/2505.17365/integrity","json":"/paper/2505.17365/citation-record.json","paper":"/paper/2505.17365"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:59:52.924061Z","title":"Blackwell approachability and no-regret learning are equivalent","venue":null,"work_id":"0af7e5c9-a4c5-4843-806c-bdd0fb1b3a8f","year":2011},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.086892Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:07a1db23ebec976457b7b653aabcf03e22b44b9dd439585153f3fe93d0a7ff13","observation_id":"d1a29ca4-d124-44fa-acbf-61fb14be8890","resolution":{"observed_at":"2026-08-07T14:59:53.010793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:52.767973Z","title":"Oracle efficient algorithms for groupwise regret","venue":null,"work_id":"192901d4-0994-4832-a98b-137e3073d1e6","year":2024},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.175361Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:f26e631836aeaa7bd8382e6661e90955b5d06664066399541ac3381cc363dc54","observation_id":"bb163019-cedd-4bb6-bbeb-ae1c2312522a","resolution":{"observed_at":"2026-08-07T14:59:52.834754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:52.639397Z","title":"Taming the monster: A fast and simple algorithm for contextual bandits","venue":null,"work_id":"dfea5612-1d0e-4e7a-99a1-91c17c11ee26","year":2014},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.252871Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:f0098be25b7cdd917508e98b20b2f8f6472fe46a3a02b093f579b73d896fc161","observation_id":"c76e0129-3eba-4731-bee6-1e10ed60b0ce","resolution":{"observed_at":"2026-08-07T14:59:52.695031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:42.363692Z","title":"Relative loss bounds for on-line density estimation with the exponential family of distributions","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.363692Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:4f16fb56f9dc7e16bb7f19b02d952cf561143563933016f813479d99e2de794c","observation_id":"1ea4ff02-b195-41ac-84d5-06284596db34","resolution":{"observed_at":"2026-08-07T14:59:42.363692Z","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":"2026-08-07T14:59:52.493979Z","title":"Smoothed online learning is as easy as statistical learning","venue":null,"work_id":"8aa926b6-3fbd-4b22-b747-6e8cbce76f75","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.446330Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:887b04bb6e66ed61f41f5328bceaa16187f6aace3c7b4e6936693b3efff54020","observation_id":"78eeea22-d0bc-44c8-a379-e065d11a5b50","resolution":{"observed_at":"2026-08-07T14:59:52.560075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:52.327772Z","title":"-entropy of convex sets and functions","venue":null,"work_id":"5ccb65b9-651d-46fd-be8f-37e9d260cf66","year":1976},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.558527Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:9217cb69cd437001a4598455ac7a03c51bbcc47392071e8e9bb38e6946e290fc","observation_id":"be0134e1-624d-4ddc-8293-9eed06cb66a0","resolution":{"observed_at":"2026-08-07T14:59:52.398185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:52.193022Z","title":"Breaking the T ^ 2/3 barrier for sequential calibration","venue":null,"work_id":"d1fbc9a3-8c34-4bbe-96d0-e360d516aac2","year":2025},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.623427Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:e1ed0edbcf1ff4b73ad8a6c6879a1458dd381c05fbf4c9e630653789f778e45b","observation_id":"650323d3-7fce-4875-9626-432f30cf1e67","resolution":{"observed_at":"2026-08-07T14:59:52.235378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:52.027887Z","title":"Learning in auctions: Regret is hard, envy is easy","venue":null,"work_id":"fc9c56b9-7b9f-4dbd-8818-0ec3a164fa54","year":2016},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.694839Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:8ecbc8fa996bff70d7cce354b04e791b9654bbb883686c55db85a5fc1d4ef9b4","observation_id":"55b62cdf-6c91-40bb-83a4-64de9d7a378d","resolution":{"observed_at":"2026-08-07T14:59:52.104759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:51.894515Z","title":"The well-calibrated bayesian","venue":null,"work_id":"0d14631c-7799-48a5-8264-cf86ec96a264","year":1982},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.776007Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:29e58ad8e458dfe5cdd2db329269d4339d3e67ef2278e34a76c19338a1d40b8e","observation_id":"ca311f52-a298-4cd8-ae88-267b27ee0be5","resolution":{"observed_at":"2026-08-07T14:59:51.954779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.05287","last_updated":"2025-07-14T18:43:51Z","snapshot_observed_at":"2026-08-14T02:51:37.403207Z","submitted_at":"2024-06-07T23:00:02Z","title":"Group-wise oracle-efficient algorithms for online multi-group learning","version":2},"cited_work":{"arxiv_id":"2406.05287","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.05287","snapshot_observed_at":"2026-08-07T14:59:45.686299Z","title":"Group-wise oracle-efficient algorithms for online multi-group learning","venue":"cs.LG","work_id":"b784288d-9af6-4ab6-aa49-b5fa7310ce3b","year":2024},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.841374Z"},"links":{"cited_paper":"/paper/2406.05287","citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:64b2b113baadf4d7b4e8024be62e73fb1d109af257675e6a4cee3b9d05a8fee3","observation_id":"555970fd-0e32-4e16-81d9-de43dcfbbfc7","resolution":{"observed_at":"2026-08-07T14:59:45.740568Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:51.763213Z","title":"Oracle-efficient online learning and auction design","venue":null,"work_id":"905e17d7-c00f-4f36-9156-809433ac04ae","year":2020},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:42.915769Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:66826f930733afd096abc19d0ba268b5bd5369df6b4792f9ed7c8cb67db07b1d","observation_id":"2e4f70fd-ebcc-4b75-a3e0-83d21215e9e3","resolution":{"observed_at":"2026-08-07T14:59:51.820340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:51.624616Z","title":"A proof of calibration via blackwell's approachability theorem","venue":null,"work_id":"a5a9fada-a0bd-4fdb-91c2-49428d593ae3","year":1999},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.000139Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:2d5076d9a6625397b4773aba4cefc055bd49577f512fb907bac6258a2591a1e9","observation_id":"115993b5-93e6-4047-b9e6-dec821a8ff28","resolution":{"observed_at":"2026-08-07T14:59:51.684171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:51.445272Z","title":"Calibration via regression","venue":null,"work_id":"e3ce218e-a8dd-4108-aaa9-e31752abab85","year":2006},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.088482Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:63e51682595a7ecba303545fd3861962790df1a46cd61d22882a7687497dd2b0","observation_id":"7e4f5763-3873-471d-ba54-c5a98eb53a95","resolution":{"observed_at":"2026-08-07T14:59:51.500573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:51.189411Z","title":"Asymptotic calibration","venue":null,"work_id":"d394b821-1d4c-4aba-9d03-312618639769","year":1998},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.183013Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:23ee24058ddd065f66c57f5321d353c9b21636e9b3a36e22166228a901f89fe9","observation_id":"92a18ed3-aa94-4c57-b266-4d49e4a7a5e0","resolution":{"observed_at":"2026-08-07T14:59:51.315331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:50.963694Z","title":"Beyond ucb: Optimal and efficient contextual bandits with regression oracles","venue":null,"work_id":"17c5d439-6fe1-4b1b-9bba-1c04efad3682","year":2020},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.275127Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:14fbabd0f190695bb584d514616697a587d3aa6261895fdda1cc27d19d5f68e5","observation_id":"7d86c54e-7020-43b7-b47b-beba3fbf6a57","resolution":{"observed_at":"2026-08-07T14:59:51.078990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:50.667457Z","title":"An easier way to calibrate","venue":null,"work_id":"fafef803-f001-4659-b4a6-dec5da1bb861","year":1999},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.436457Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:3febb2519642c2aec163cdb76019950e94563b4a5e0481b4f17321fd1892129e","observation_id":"9a0d11e6-2da3-417f-bb09-f6f1aa6d6e16","resolution":{"observed_at":"2026-08-07T14:59:50.819246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:50.473676Z","title":"Oracle efficient online multicalibration and omniprediction","venue":null,"work_id":"609d1e31-d1f3-4387-b5ab-6bfc240e2118","year":2024},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.540469Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:e0b5dba748e83021e3e776f185f9cd21a217e4462453f5b0f896ad8e89d81c5b","observation_id":"6d419b92-1e2e-4566-89cb-cf8741e3038d","resolution":{"observed_at":"2026-08-07T14:59:50.576538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:50.180093Z","title":"Multicalibration as boosting for regression","venue":null,"work_id":"90306ccd-400f-48b1-a0ba-083140609c6a","year":2023},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.622755Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:46fe6854bb7057bc09efa1d1566a22a2b43ac68de5a61bb58a78618ae7b3105c","observation_id":"4d285ca7-e55b-4b14-936d-2c3c2f79fb01","resolution":{"observed_at":"2026-08-07T14:59:50.361007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:49.972658Z","title":"Omnipredictors","venue":null,"work_id":"8f4ace1f-de35-4314-98f0-b10435c18579","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.670904Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:7861ad0d0b7d07d20faf6943aca51bbc200c2d3d27a222a7026c4a909e66c63d","observation_id":"322b1a36-c54d-4eef-b622-119d0907d53e","resolution":{"observed_at":"2026-08-07T14:59:50.039248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:49.693166Z","title":"Swap agnostic learning, or characterizing omniprediction via multicalibration","venue":null,"work_id":"f0a8d53a-5bc3-4f84-9ad1-724f917cd5f7","year":2023},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.749627Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:83625f8167c4efb8d32e4e015bbdbfbb91ccb9ca4edfcef42db49430e624c9b1","observation_id":"b9ee95f1-68e9-4e70-a53a-52521618feac","resolution":{"observed_at":"2026-08-07T14:59:49.857790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:49.489475Z","title":"Covering numbers for convex functions","venue":null,"work_id":"e7c81675-bbaa-4438-8b11-ece27fc13b95","year":1957},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.870913Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:cbf0637c4bdff944cf86fdee30e5089bafde1f2423f1637d32def66d78b081bc","observation_id":"2fbf767b-6006-494a-9685-537b404a3b3f","resolution":{"observed_at":"2026-08-07T14:59:49.570805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:49.339652Z","title":"Pai, and Aaron Roth","venue":null,"work_id":"64fc4c6a-ee81-4707-a9e6-00f5a4918575","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:43.938938Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:6f7e532599c1e2e11d1e06be32c46079dd8a7e7d429d028d4f8f1479f676b31f","observation_id":"adb50f3a-da7a-434e-9761-51f43356caab","resolution":{"observed_at":"2026-08-07T14:59:49.405741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:49.119551Z","title":"Oracle-efficient online learning for smoothed adversaries","venue":null,"work_id":"6a6200c2-92a7-4d57-98cb-7c054affd31b","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.007760Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:6096a08c3fff0e3abdeb4d4ab715bf0508b1d45fa2fdd560974261db8c51e413","observation_id":"5ec8d71b-3845-4a41-807e-bf1153819fac","resolution":{"observed_at":"2026-08-07T14:59:49.244685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.05863","last_updated":"2023-02-11T11:05:00Z","snapshot_observed_at":"2026-08-13T14:27:56.289429Z","submitted_at":"2022-09-13T10:24:54Z","title":"Calibrated Forecasts: The Minimax Proof","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.05863","snapshot_observed_at":"2026-08-07T14:59:44.067053Z","title":"Calibrated forecasts: The minimax proof","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.067053Z"},"links":{"cited_paper":"/paper/2209.05863","citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:b68f2bfc6e61bde7be13fb5d4fd265efe1ff713c793a8d0d65d582c8930c1bfe","observation_id":"bf5f7961-ccb2-4121-80c2-cea7888b0a2b","resolution":{"observed_at":"2026-08-07T14:59:44.067053Z","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":"2026-08-07T14:59:48.972045Z","title":"A simple adaptive procedure leading to correlated equilibrium","venue":null,"work_id":"7ccf814c-be85-41b1-b34a-d23930198255","year":2000},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.123526Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:fc7f12a99f8c3b67b152446021b5d81d31192e2b6bafd699384a9e28f825e23f","observation_id":"d975cd03-c709-41a8-9bde-9f0cdafe4db2","resolution":{"observed_at":"2026-08-07T14:59:49.034585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:48.762327Z","title":"A large-deviation inequality for vector-valued martingales","venue":null,"work_id":"8f1a1836-8809-481d-8a52-75a679bfadf6","year":2005},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.190008Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:331ce01b35f64ae7bd0ce683b279b63a5469af26f8c56b51ce3d288f0fed71c3","observation_id":"136bf9d7-a5dd-4687-b351-a24a32ce239c","resolution":{"observed_at":"2026-08-07T14:59:48.855021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:48.594306Z","title":"The computational power of optimization in online learning","venue":null,"work_id":"f5ff2b67-fd4b-401f-a271-f61ee82e7146","year":2016},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.240018Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:2c3b649d84172f5550258db146c4f97a8815cdff0e08953c6ac002715bf9f819","observation_id":"d6aa811a-ff3b-4928-8073-d57b614c537b","resolution":{"observed_at":"2026-08-07T14:59:48.676566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:44.282385Z","title":"Introduction to online convex optimization","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.282385Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:af77c7f61f61c1c4a8b155e32b083fae66c11ad99374040c14a7d4c5406d45fb","observation_id":"a8441279-500a-483b-8392-858ea8dd30c3","resolution":{"observed_at":"2026-08-07T14:59:44.282385Z","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":"2026-08-07T14:59:48.454620Z","title":"Multicalibration: Calibration for the (computationally-identifiable) masses","venue":null,"work_id":"10210ed0-5f7a-47b6-96b5-c7035e3c78db","year":1939},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.382355Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:f6a2b80abd7e2cc15af1df5bf3c5c2a93e6b0c076a8acc6973b4f219fca1d11f","observation_id":"d6f6c432-c819-4c8a-9bbd-59bc35acd661","resolution":{"observed_at":"2026-08-07T14:59:48.519174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:48.252885Z","title":"Moment multicalibration for uncertainty estimation","venue":null,"work_id":"3d3fcdc2-b784-4548-81ab-0e08a19a5358","year":2021},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.494988Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:075dbd11ab75d4c9254be7bfad9d22621222fbcaa45ba215c73f0242ffd29041","observation_id":"37fbdbcc-7ba0-46b9-a502-268ba8c08149","resolution":{"observed_at":"2026-08-07T14:59:48.329950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:48.055076Z","title":"Efficient algorithms for online decision problems","venue":null,"work_id":"76f3eab8-8b81-4b86-b1e3-4d42f47af448","year":2005},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.580887Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:462faa88c92b86d70e28482da0c508a1b0d7c051ee4a64d94840e0b732862b89","observation_id":"c2fb28c3-aac3-4c98-af75-88ac91a146b2","resolution":{"observed_at":"2026-08-07T14:59:48.128104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:47.850695Z","title":"Multiaccuracy: Black-box post-processing for fairness in classification","venue":null,"work_id":"26102bd8-bb59-4fae-b162-abe55d4eaad8","year":2019},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.657505Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:bd43147adf9fec597dedac875beac3c0ccec4bda8bbae167a0020e3cdfd4cac9","observation_id":"42cb4f49-3d7a-460a-9a97-aeb97767c2cf","resolution":{"observed_at":"2026-08-07T14:59:47.960722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:47.618443Z","title":"Universal adaptability: Target-independent inference that competes with propensity scoring","venue":null,"work_id":"b9fd2134-3a61-413e-bd43-91834d7516ae","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.724140Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:b0595576f6b3f30595dee3f6cda0696f72c4ac85794d45fa67312f146ec8f02b","observation_id":"9909851a-fbf2-4df6-9491-cc6d7829898e","resolution":{"observed_at":"2026-08-07T14:59:47.718146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:47.474835Z","title":"Online minimax multiobjective optimization: Multicalibeating and other applications","venue":null,"work_id":"98e580ae-3e88-48db-b785-a651e152aa53","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.777111Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:8b49e6f52a4b44a8a2c5914815f03ebc159ade6ba5269dd2111857cc625f0e2c","observation_id":"ddbf0ecf-0759-4753-b88a-2b3b683992c1","resolution":{"observed_at":"2026-08-07T14:59:47.538692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:47.241743Z","title":"High-dimensional prediction for sequential decision making","venue":null,"work_id":"90d4aa94-3ca9-4733-9741-f226585a1e2c","year":2025},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.870049Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:5aad65f5ecffb741a5baf7720c2f675b81a355b311c534afc16071ce786c39a1","observation_id":"43f32726-e72f-4263-92af-e0b7f9c2ca93","resolution":{"observed_at":"2026-08-07T14:59:47.403381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:47.010922Z","title":"Calibration and internal no-regret with random signals","venue":null,"work_id":"adcda788-e43d-45d3-bf75-d3124cfdee3a","year":2009},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:44.957049Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:c3511e1d932405ca7c450f2118f150532b445b49b409373c1a47a8a6eccbe134","observation_id":"4fea4863-4530-4725-800c-d87e6752b62a","resolution":{"observed_at":"2026-08-07T14:59:47.084287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:46.775294Z","title":"Stronger calibration lower bounds via sidestepping","venue":null,"work_id":"f6b557ed-f1a6-4260-afad-78282f3094f6","year":2021},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:45.022391Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:55984acac9c2cf2297bcd3d693a97a80f366afbd3bb11b6c0c7fd664b9b23dee","observation_id":"9368b38f-4b58-4399-9b60-3a8f5ab2feb4","resolution":{"observed_at":"2026-08-07T14:59:46.900799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:46.529354Z","title":"The reproducible properties of correct forecasts","venue":null,"work_id":"5436f40f-8115-4a9b-aa08-55b50e1d08bd","year":2003},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:45.160070Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:8dd7f1a67572c89e95a918b30b5c36f7a4fbd97f4fe2a9de90222b35a6beb9e6","observation_id":"f65f1ba7-b74a-415d-af5a-85d1949275c1","resolution":{"observed_at":"2026-08-07T14:59:46.647545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:46.282929Z","title":"Calibration with many checking rules","venue":null,"work_id":"c3519969-19e9-48af-90b7-a7e98f9a1587","year":2003},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:45.283682Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:12f107279a9f0574ac8c5b5c2e232cbd18fecb9ad58a6d42e3ccdd2a74dff5a4","observation_id":"ad927b99-c03c-4560-b5a5-213ae34106d7","resolution":{"observed_at":"2026-08-07T14:59:46.384087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:46.059792Z","title":"Efficient algorithms for adversarial contextual learning","venue":null,"work_id":"b281093e-d51f-4745-b8f7-5fb9086bdf0e","year":2016},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:45.398416Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:ad7a241da6855387ea35b8d0a85546149959e5e24658f81b1bb9f3675fa1cb6d","observation_id":"c24bc83b-fa23-4a48-af68-d03baec64337","resolution":{"observed_at":"2026-08-07T14:59:46.181222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T14:59:45.866184Z","title":"Adaptive oracle-efficient online learning","venue":null,"work_id":"6e84ef7d-7ab4-4595-8bfd-130a4aa2dcc3","year":2022},"citing_paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T14:59:45.532689Z"},"links":{"citing_paper":"/paper/2505.17365"},"observation_digest":"sha256:1338b365ecd83ddbcbfec444385f61332398b0e677bdd226e1e334e617ff0ac5","observation_id":"3e091a90-ab45-45e1-8967-492109761c74","resolution":{"observed_at":"2026-08-07T14:59:45.957532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.17365","last_updated":"2025-05-29T02:21:58Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T15:17:23.981805Z","submitted_at":"2025-05-23T00:37:49Z","title":"Improved and Oracle-Efficient Online $\\ell_1$-Multicalibration"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":1,"verified_fuzzy":37},"total_outbound_references":41},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.17365."}