{"as_of":"2026-08-10T16:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:06ce62baefe2068a78dd14245995ae0906c94b25f0c6d15b10632cfa477c707d","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T15:22:10.261211Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2509.20114/citation-record","integrity":"/paper/2509.20114/integrity","json":"/paper/2509.20114/citation-record.json","paper":"/paper/2509.20114"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.258453Z","title":"Lemma B.1.For anyδ∈(0,1)and for anyq∈ T t∈[T] b∆t(Pt), Algorithm 1 attains: TX t=1 bℓ⊤ t (bqt −q)≤L ln |X| 2|A| η +η|X||A|T+ ηLln L δ γ , with probability at least1−δ","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.258453Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:9b559583c76170680179f1052332dced155e972d8a0d525cdfa46cda984206d2","observation_id":"a60c335d-cb89-4eb5-ac27-02fd3efae8f2","resolution":{"observed_at":"2026-08-04T15:22:10.258453Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.233504Z","title":"Aviv Rosenberg and Yishay Mansour","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.233504Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:94c8014c41c87171ff97ad89cf12accd814efb589b68c56c4a446f65cac2c7a0","observation_id":"569961bc-66eb-4e7a-83c8-76ffeda4b0ac","resolution":{"observed_at":"2026-08-04T15:22:10.233504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14372","last_updated":"2024-09-26T13:23:54Z","snapshot_observed_at":"2026-08-10T13:04:11.346032Z","submitted_at":"2024-05-23T09:48:48Z","title":"Learning Constrained Markov Decision Processes With Non-stationary Rewards and Constraints","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14372","snapshot_observed_at":"2026-08-04T15:22:10.240141Z","title":"Online learning in CMDPs: Handling stochastic and adversarial constraints","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.240141Z"},"links":{"cited_paper":"/paper/2405.14372","citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:b4579564765c6afbee46acf4f14333a6cde8227c1c0f4fa47870ec15f43dba49","observation_id":"4373585a-8186-4eab-be09-5558d2862fe7","resolution":{"observed_at":"2026-08-04T15:22:10.240141Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.249378Z","title":"The authors analyze two approaches, both providing sub- linear regret and cumulative constraint violation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.249378Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:288879999f0038fda006c682f571993499c46a8cd61fa523408ed77faddb04bd","observation_id":"6735a635-8dc9-48ae-a763-32af00432d41","resolution":{"observed_at":"2026-08-04T15:22:10.249378Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.252298Z","title":"This algorithm achieves eO(T 3 4 ) regret and guarantees that the cumulative constraint violation remains below a certain threshold with a given probability","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.252298Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:a32c729d3a44a88e898b2ea475cc27bc2556dd46e1065238104360c3cc29cdcc","observation_id":"cc09dbf4-8760-4d98-a818-b2658c2f5f88","resolution":{"observed_at":"2026-08-04T15:22:10.252298Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.255540Z","title":"The first best-of-both- worlds algorithm for online learning in episodic CMDPs was proposed by Stradi et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.255540Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:863102e20a6050aa258fda2211d9221760d78d42e0f1fc4a003e93fd692c61b9","observation_id":"203f5f2a-5e65-467f-b2fe-3ac8e50fc338","resolution":{"observed_at":"2026-08-04T15:22:10.255540Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.261211Z","title":"In the stochastic setting, Algorithm 1 guarantees with probability at least 1−16δ: Vt ≤18L|X| r 2t|A|ln 2mT|X||A| δ ∀t∈[T]","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.261211Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:1e22106463ba594402d99bf98564240e0a427fd1a5509376f265826a5177f43e","observation_id":"b2b2ef56-77a9-4708-bbfd-04238ebcf7d2","resolution":{"observed_at":"2026-08-04T15:22:10.261211Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.237090Z","title":"URLhttps://proceedings.neurips.cc/paper/2019/file/ a0872cc5b5ca4cc25076f3d868e1bdf8-Paper.pdf","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.237090Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:ba1eeb5e093bfbfe60b9ee675bd75baf85c5b998abe9530282bc39a597f1cfbc","observation_id":"02f1a4b9-f96a-4213-bc20-cf82780c2fd4","resolution":{"observed_at":"2026-08-04T15:22:10.237090Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:09.694108Z","title":"Mohammad Gheshlaghi Azar, Ian Osband, and R´ emi Munos","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2008,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:09.694108Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:5f3eeb20b48b237d22987971391c4c6ce5ce07aefcc064f9e2b2cbf91be2cab6","observation_id":"34b9996a-d294-40e2-9f7e-92c20fe929b6","resolution":{"observed_at":"2026-08-04T15:22:09.694108Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.246588Z","title":"the algorithm receives the complete loss/reward information","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.246588Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:2f9120ead056a898ec484a449692c116f7e2f56a4c8f0cf212dc2f57257eeb9d","observation_id":"5b8aad86-3091-4962-acdd-1bab78d4805c","resolution":{"observed_at":"2026-08-04T15:22:10.246588Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:10.243720Z","title":"13 Contents 1 Introduction 1 1.1 Original Contributions","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.243720Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:ccb32eb26d9dc334a0fced542405c237d72796c55b7657ce2f133719aa931660","observation_id":"2c4ea8fa-317f-45f2-b760-dfa6fba25a97","resolution":{"observed_at":"2026-08-04T15:22:10.243720Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:09.982015Z","title":"Gergely Neu, Andras Antos, Andr´ as Gy¨ orgy, and Csaba Szepesv´ ari","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:09.982015Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:6a2f6cd6aec28a6f9a90a62e41990af27da847968a41c5e4f813d4f119be0935","observation_id":"ba09c85e-9df3-46d6-a408-475eb95d0af7","resolution":{"observed_at":"2026-08-04T15:22:09.982015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.13213","last_updated":"2026-06-21T08:13:27Z","snapshot_observed_at":"2026-07-06T08:47:45.187408Z","submitted_at":"2019-12-31T08:16:31Z","title":"Online Learning: A Modern Introduction Using Convex Optimization","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.13213","snapshot_observed_at":"2026-08-04T15:22:10.230161Z","title":"Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, and Heinrich Jiang","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:10.230161Z"},"links":{"cited_paper":"/paper/1912.13213","citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:b0054ee66b59ac73c0ffc1542928548cd5d28a15be8a95eeb5f654547ce42229","observation_id":"86531a45-37d1-4ab5-8b3b-a6267f30a5c9","resolution":{"observed_at":"2026-08-04T15:22:10.230161Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.02189","last_updated":"2020-03-04T17:03:56Z","snapshot_observed_at":"2026-08-05T18:34:50.706165Z","submitted_at":"2020-03-04T17:03:56Z","title":"Exploration-Exploitation in Constrained MDPs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.02189","snapshot_observed_at":"2026-08-04T15:22:09.724181Z","title":"Eyal Even-Dar, Sham M Kakade, and Yishay Mansour","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:09.724181Z"},"links":{"cited_paper":"/paper/2003.02189","citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:82884bb3683e17e30bc4d8c6e0a78f501f15451872329083c82dee6660a56470","observation_id":"571673aa-a36d-4155-abbd-62165f56dc9a","resolution":{"observed_at":"2026-08-04T15:22:09.724181Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T15:22:09.865668Z","title":"Safe reinforcement learning on autonomous vehicles","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints","version":3},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-04T15:22:09.865668Z"},"links":{"citing_paper":"/paper/2509.20114"},"observation_digest":"sha256:2e345272a96c35155b32784af853cf8d5f1562cafe30e7201cb5ed783f1264eb","observation_id":"054b12b5-6740-4e04-8b42-a24eaf4f41b6","resolution":{"observed_at":"2026-08-04T15:22:09.865668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.20114","last_updated":"2026-07-13T10:42:17Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T15:22:08.373675Z","submitted_at":"2025-09-24T13:38:32Z","title":"Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":15},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2509.20114."}