Paper Citation Record · LEDGER

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints

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.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.20114 v3

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:22:10.261211Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a60c335d-cb89-4eb5-ac27-02fd3efae8f2 · outbound

This paper cites 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.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints 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

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.258453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569961bc-66eb-4e7a-83c8-76ffeda4b0ac · outbound

This paper cites Aviv Rosenberg and Yishay Mansour.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Aviv Rosenberg and Yishay Mansour

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.233504Z

Source-reported events for the cited work

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Observation 4373585a-8186-4eab-be09-5558d2862fe7 · outbound

This paper cites Learning Constrained Markov Decision Processes With Non-stationary Rewards and Constraints.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Learning Constrained Markov Decision Processes With Non-stationary Rewards and Constraints

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.240141Z

Source-reported events for the cited work

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Observation 6735a635-8dc9-48ae-a763-32af00432d41 · outbound

This paper cites The authors analyze two approaches, both providing sub- linear regret and cumulative constraint violation.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints The authors analyze two approaches, both providing sub- linear regret and cumulative constraint violation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.249378Z

Source-reported events for the cited work

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Observation cc09dbf4-8760-4d98-a818-b2658c2f5f88 · outbound

This paper cites This algorithm achieves eO(T 3 4 ) regret and guarantees that the cumulative constraint violation remains below a certain threshold with a given probability.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints This algorithm achieves eO(T 3 4 ) regret and guarantees that the cumulative constraint violation remains below a certain threshold with a given probability

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.252298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 203f5f2a-5e65-467f-b2fe-3ac8e50fc338 · outbound

This paper cites The first best-of-both- worlds algorithm for online learning in episodic CMDPs was proposed by Stradi et al.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints The first best-of-both- worlds algorithm for online learning in episodic CMDPs was proposed by Stradi et al

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.255540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2b2ef56-77a9-4708-bbfd-04238ebcf7d2 · outbound

This paper cites 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].

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints 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]

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.261211Z

Source-reported events for the cited work

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Observation 02f1a4b9-f96a-4213-bc20-cf82780c2fd4 · outbound

This paper cites URLhttps://proceedings.neurips.cc/paper/2019/file/ a0872cc5b5ca4cc25076f3d868e1bdf8-Paper.pdf.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints URLhttps://proceedings.neurips.cc/paper/2019/file/ a0872cc5b5ca4cc25076f3d868e1bdf8-Paper.pdf

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.237090Z

Source-reported events for the cited work

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Observation 34b9996a-d294-40e2-9f7e-92c20fe929b6 · outbound

This paper cites Mohammad Gheshlaghi Azar, Ian Osband, and R´ emi Munos.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Mohammad Gheshlaghi Azar, Ian Osband, and R´ emi Munos

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:09.694108Z

Source-reported events for the cited work

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Observation 5b8aad86-3091-4962-acdd-1bab78d4805c · outbound

This paper cites the algorithm receives the complete loss/reward information.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints the algorithm receives the complete loss/reward information

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.246588Z

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Observation 2c4ea8fa-317f-45f2-b760-dfa6fba25a97 · outbound

This paper cites 13 Contents 1 Introduction 1 1.1 Original Contributions.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints 13 Contents 1 Introduction 1 1.1 Original Contributions

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.243720Z

Source-reported events for the cited work

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Observation ba09c85e-9df3-46d6-a408-475eb95d0af7 · outbound

This paper cites Gergely Neu, Andras Antos, Andr´ as Gy¨ orgy, and Csaba Szepesv´ ari.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Gergely Neu, Andras Antos, Andr´ as Gy¨ orgy, and Csaba Szepesv´ ari

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:09.982015Z

Source-reported events for the cited work

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Observation 86531a45-37d1-4ab5-8b3b-a6267f30a5c9 · outbound

This paper cites Online Learning: A Modern Introduction Using Convex Optimization.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Online Learning: A Modern Introduction Using Convex Optimization

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:10.230161Z

Source-reported events for the cited work

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Observation 571673aa-a36d-4155-abbd-62165f56dc9a · outbound

This paper cites Exploration-Exploitation in Constrained MDPs.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Exploration-Exploitation in Constrained MDPs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:09.724181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 054b12b5-6740-4e04-8b42-a24eaf4f41b6 · outbound

This paper cites Safe reinforcement learning on autonomous vehicles.

Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints Safe reinforcement learning on autonomous vehicles

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T15:22:09.865668Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.