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Paper Citation Record · LEDGER

Learning Adversarial MDPs with Stochastic Hard Constraints

As of 17 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 2026-08-17T06:30:58.91139+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=sha256:37845b3deb95814ecaaa65884991569c099f01dfcc4a575cc8074da12cef2306

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=sha256:2ed0ea4bcf4a9d4bd1135ae226c6233c4364601336035705a78db452e5b8bc8e

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=sha256:4033b761a9ebbcafe9812979aa403c7ac6382ef07a221eb59038409a54a891d9

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-12T02:23:56.057336Z digest=sha256:483a0db5f3ccb9a9c3733b4a22a896cf9117c9e3e74d7a0256b77a220e76bacf

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-12T04:04:36.278591Z digest=sha256:aa8acfcc2997029ac0f6cf5f7b1e971889e224cf77d92aebfe65d373de039b6e

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=sha256:629b538d982ffc571973d53c44237e4e9bde67c14d9df1d35f97d1978249cd50