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Paper Citation Record · LEDGER

On Lai's Upper Confidence Bound in Multi-Armed Bandits

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.02279.

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

pith.paper-citation-record.v1
2410.02279 v2

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:49:45.410543Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T20:08:48.076096Z

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 de269d7c-e0f9-4aca-8285-636085728be5 · inbound

Selective Reviews of Bandit Problems in AI via a Statistical View cites this paper.

Selective Reviews of Bandit Problems in AI via a Statistical View On Lai's Upper Confidence Bound in Multi-Armed Bandits

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-11T23:49:45.410543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:49:45.410543Z digest=sha256:58c96dc2a6249bf1eda79247be2747580c920ab83e82ae82e16ec14f9c0b3b4f

Observation b6139804-bf5e-4251-9b83-38ce046af334 · inbound

UCB algorithms for multi-armed bandits: Precise regret and adaptive inference cites this paper.

UCB algorithms for multi-armed bandits: Precise regret and adaptive inference On Lai's Upper Confidence Bound in Multi-Armed Bandits

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:08:48.088797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T20:08:47.177105Z digest=sha256:60d0dea52fa01be796623fa6276d642bb1bb81ee55e015e9c5a5a1e9744351ee