Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T18:54:01.147324Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.17201.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T18:54:01.147324Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
37 of 37 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7151ce36-21b7-4331-9ea6-7279ad572995 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Al Marjani and A
Reference 1
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Observation 06e02925-65d5-44b7-a941-788000b5515e · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Al Marjani, A
Reference 2
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Observation eb8f7d5f-4cd3-4159-bab6-483cb77255c7 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Policy Testing in Markov Decision Processes
Reference 3
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Observation 5db72b6e-b558-44fb-84bb-66656e05f635 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Berge.Topological Spaces: Including a Treatment of Multi-Valued Functions, Vector Spaces, and Convexity
Reference 4
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Observation d909eea6-b31c-4031-a7f4-2b717132859b · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning The regret lower bound for communicating Markov Decision Processes
Reference 5
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Observation 57780a37-c1e1-4079-bbe6-c2a72904419b · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Boucheron, G
Reference 6
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Observation 35b958e0-4312-4ee4-8b38-d8bd4a94e922 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 7
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Observation cc0fdbbe-2b6f-468b-9fab-af3a2ff57e66 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c7876929-fb53-45a4-9151-039a347cdc81 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 9
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Observation 89863d45-3678-4211-85ce-8f2e6f2a8cd6 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 10
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Observation 8f0bcc96-f663-41c7-b677-5d9384688533 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Degenne and W
Reference 11
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Observation b9d2103a-99e4-478c-a38f-eebcc5d336bb · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Degenne, W
Reference 12
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Observation 3d740a2c-859d-47ca-859f-242de7a9d63c · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Garivier and E
Reference 13
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Observation 03a5005e-b5c8-4b51-affd-a8ca7f56596f · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Thresholding Bandit for Dose-ranging: The Impact of Monotonicity
Reference 14
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Observation ea5a2da7-1be2-42c6-90c7-e54f0ed970c6 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 15
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Observation 0932b424-0528-462e-8a90-dcd389e59d9f · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Jonsson, E
Reference 16
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Observation 1d2e93fe-fe6a-480f-ab5a-d8737b0ea7cb · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Jourdan and A
Reference 17
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Observation 1f0be86c-19be-4cb5-8176-6cacd2e5c25f · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Jourdan, R
Reference 18
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Observation 57eccf5b-b2b7-4de4-970c-f440032526d9 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Kaufmann, P
Reference 19
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Observation d906c45c-3b27-448f-be8d-5343fa621c18 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Lazzaro and C
Reference 20
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Observation 842bcfb4-453a-442e-882f-d3e4cf19f9a7 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 21
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Observation dc50e33e-8360-45a6-9365-1d9cb6cbf796 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Poiani, M
Reference 22
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Observation 10d17296-4c7f-4280-b064-9b74ca0f8251 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Poiani, M
Reference 23
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Observation a3557330-acb1-4377-9e61-ef785a6d2b92 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 24
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Observation 661319d6-b19e-4270-8ce8-866f141e0195 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Reference 25
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Observation 1b4326d2-0013-4adf-a545-e70733671d2e · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Russo and A
Reference 26
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Observation 224278e4-ab14-4781-9513-404ffd466581 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Russo and F
Reference 27
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Observation f0043074-c72f-4304-8351-3d4601eaf280 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Pure Exploration with Feedback Graphs
Reference 28
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Observation 2db139a3-37fb-4422-b44f-c4ca9c94165a · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 29
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Observation 50d7c8a2-7619-4abe-9d3d-2db699ddff46 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Asymptotically Optimal Sequential Testing with Markovian Data
Reference 30
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Observation c8a9d37c-bec9-4521-9c69-4ffcc2cfc9e0 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 31
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Observation a29c040a-498a-4498-9d0d-dd22925ba511 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 32
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Observation 73eadf8b-3c6d-4b0a-bfa7-1eb5171673f6 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Taupin, Y
Reference 33
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Observation 78ae6ba3-d871-475b-9c6b-9e31467066b0 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Tuynman and R
Reference 34
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Observation dc1d2a00-e8be-4281-88aa-fd7bc1184742 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Zalinescu
Reference 35
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Observation e79e6aa5-05e1-4189-afa2-4290b4bd6dd3 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Unresolved cited work
Reference 36
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Observation c115e5c2-e857-4ce1-92bb-b79578246156 · outbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning Lemma 42.Let Ω⋆(M) := ( ω∈Ω(M) inf M′∈Alt(M) X s,a ω(s, a)KL(P(s, a), P′(s, a)) = (T⋆(M))−1 )
Reference 37
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No inbound Pith citation observations are available.