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Paper Citation Record · LEDGER

Ensemble sampling for linear bandits: small ensembles suffice

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.08376.

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

pith.paper-citation-record.v1
2311.08376 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T16:43:54.405426Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:09:30.498865Z

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 99373099-d1a9-4812-a0fb-0edd07e0eb66 · inbound

Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates cites this paper.

Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates Ensemble sampling for linear bandits: small ensembles suffice

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:36:15.092006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T16:43:54.405426Z digest=sha256:593fb0f659aa2098564beed02bbe3dcbde4e0b2a36a34fff5a1d4a984580e1d7

Observation 5374735b-6114-4681-9df8-05501013a69e · inbound

Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning cites this paper.

Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning Ensemble sampling for linear bandits: small ensembles suffice

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:09:30.500673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-26T18:19:02.314185Z digest=sha256:0f15f39a4ffae40a3dea18c55e6663f0ec9059d53e42a77cd36a5971a5d9140c