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Paper Citation Record · LEDGER

Learning Adversarial MDPs with Stochastic Hard Constraints

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2403.03672.

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

pith.paper-citation-record.v1
2403.03672 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:52.208911Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:41:27.789065Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0500cb62-2128-4fe6-a506-10c64ffda4f7 · inbound

Data-Dependent Regret Bounds for Constrained MABs cites this paper.

Data-Dependent Regret Bounds for Constrained MABs Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T14:16:52.208911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:52.208911Z digest=sha256:719732f1ad4be491c272d31eb0a129ad0659c4e0dba6862bc831c79b6632850d

Observation a182d344-fcc4-42ee-bf95-7cbc40d03d95 · inbound

An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints cites this paper.

An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T13:35:51.044652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:35:51.044652Z digest=sha256:fecad7404555c81101ba28ac143423da7ce06eae91780970ae9ceb4d43839557

Observation a48b5e45-c020-4f85-983c-bea6457fb9b8 · inbound

No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! cites this paper.

No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T00:44:27.212457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:44:27.212457Z digest=sha256:536bb1c92708d290a450089c43b3d55e9a42b17e23fc8cfa35af0e01a5676352

Observation e25465a4-fbc9-4f66-99a5-5fa98b70a251 · inbound

Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time cites this paper.

Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:41:27.794159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T02:23:56.057336Z digest=sha256:3eb2920c93de77f7a8a7811597113e70c190d8efddc8f2492322b19f506f6fd4

Observation bb51d065-4e69-4969-b200-8c17d5295f61 · inbound

Online Resource Allocation With General Constraints cites this paper.

Online Resource Allocation With General Constraints Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:41:31.772007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T04:04:36.278591Z digest=sha256:7b33434736a4ffe659d65b8f2e34da2da5836748dd5592daf4612ce912fa7a92

Observation f6298c77-7829-4a96-a705-ac0563ec262c · inbound

Decoupling Corruption and Horizon in Robust Contextual Pricing cites this paper.

Decoupling Corruption and Horizon in Robust Contextual Pricing Learning Adversarial MDPs with Stochastic Hard Constraints

Reference 41

Resolution
unresolved
no resolver link, observed 2026-07-14T06:16:13.601515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T06:16:13.601515Z digest=sha256:b9e655666b614c9018cb74274a5960bec711f2f36d415bb3501e0570b1e94060