Paper Citation Record · LEDGER

Learning in Markovian bandits with non-observable states and constrained decision epochs

As of 10 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2606.27448.

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

pith.paper-citation-record.v1
2606.27448 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T01:20:21.181843Z

measured 12 of 12 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

12 of 12 outbound references displayed

verified exact3
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07e44a8e-f684-4c2a-8b50-4baeb1cbc319 · outbound

This paper cites neurips.cc/paper_files/paper/2019/file/88fee0421317424e4469f33a48f50cb0-Paper.pdf.

Learning in Markovian bandits with non-observable states and constrained decision epochs neurips.cc/paper_files/paper/2019/file/88fee0421317424e4469f33a48f50cb0-Paper.pdf

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0270dfa6-9c1c-4e49-8df8-678260715a3c · outbound

This paper cites The regret lower bound for communicating Markov Decision Processes.

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 767d66c0-aad8-4698-a560-33ac382859f2 · outbound

This paper cites Thompson Sampling in Non-Episodic Restless Bandits.

Learning in Markovian bandits with non-observable states and constrained decision epochs Thompson Sampling in Non-Episodic Restless Bandits

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T18:55:59.139261Z

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 82796a65-172f-4a47-b398-e61fd1541736 · outbound

This paper cites Logarithmic weak regret of non-bayesian restless multi-armed bandit.

Learning in Markovian bandits with non-observable states and constrained decision epochs Logarithmic weak regret of non-bayesian restless multi-armed bandit

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0644c29f-677f-4677-a41f-3abe3660a766 · outbound

This paper cites Learning in a changing world: Restless multiarmed bandit with unknown dynamics.IEEE Transactions on Information Theory, 59(3):1902–1916,.

Learning in Markovian bandits with non-observable states and constrained decision epochs Learning in a changing world: Restless multiarmed bandit with unknown dynamics.IEEE Transactions on Information Theory, 59(3):1902–1916,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74e3f11d-0540-4342-bec9-7f8b67a8098c · outbound

This paper cites Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP.

Learning in Markovian bandits with non-observable states and constrained decision epochs Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-01T18:55:59.142261Z

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 a7a8a8ea-be33-49cf-90fe-5610276eef58 · outbound

This paper cites As a direct consequence of Lemma A.1, the regret can be approximated by ∑T−1 t=1 (g∗−R(t)), where g∗= maxa∈Aga.

Learning in Markovian bandits with non-observable states and constrained decision epochs As a direct consequence of Lemma A.1, the regret can be approximated by ∑T−1 t=1 (g∗−R(t)), where g∗= maxa∈Aga

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c3aa586-26cf-464e-b470-16fd06458b68 · outbound

This paper cites Using a change of measure (Appendix C.1, see Theorems C.1 and C.2), we can bind the behavior of the learning algorithm inM1 to its behavior onM2.

Learning in Markovian bandits with non-observable states and constrained decision epochs Using a change of measure (Appendix C.1, see Theorems C.1 and C.2), we can bind the behavior of the learning algorithm inM1 to its behavior onM2

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f299c58-78d3-45a8-becd-32efe5e06374 · outbound

This paper cites 31 Initial, trueMa Ma Possible alternativeMε a Mε a s∞ ε R= 1 Figure 6: An illustration of the transformationMε a.

Learning in Markovian bandits with non-observable states and constrained decision epochs 31 Initial, trueMa Ma Possible alternativeMε a Mε a s∞ ε R= 1 Figure 6: An illustration of the transformationMε a

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10f814b7-1563-4d38-bc34-51b131b4e9c5 · outbound

This paper cites an unresolved cited work.

Learning in Markovian bandits with non-observable states and constrained decision epochs Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 338e0e30-e0fc-47be-86b7-9481704e84a1 · outbound

This paper cites The dominant termC0 b √ |A|Tlog(T)scales exclusively with the span bound.

Learning in Markovian bandits with non-observable states and constrained decision epochs The dominant termC0 b √ |A|Tlog(T)scales exclusively with the span bound

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a5851e5-a193-4011-b2c7-7a4270cbdbe0 · outbound

This paper cites an unresolved cited work.

Learning in Markovian bandits with non-observable states and constrained decision epochs Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T01:20:21.181843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.