Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The regret lower bound for communicating Markov Decision Processes
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.13013.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:41:52.317140Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T18:55:59.134962Z
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 b97480b8-281b-492d-a57e-531ff7779aa3 · inbound
Asymptotically optimal regret in communicating Markov decision processes cites this paper.
Asymptotically optimal regret in communicating Markov decision processes The regret lower bound for communicating Markov Decision Processes
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:41:52.317140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0270dfa6-9c1c-4e49-8df8-678260715a3c · inbound
Learning in Markovian bandits with non-observable states and constrained decision epochs cites this paper.
Learning in Markovian bandits with non-observable states and constrained decision epochs The regret lower bound for communicating Markov Decision Processes
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T18:55:59.136652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d909eea6-b31c-4031-a7f4-2b717132859b · inbound
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning cites this paper.
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning The regret lower bound for communicating Markov Decision Processes
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T18:53:58.706383Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.