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Paper Citation Record · LEDGER

Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.13180.

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

pith.paper-citation-record.v1
2311.13180 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 2026-08-11T23:49:45.254987Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:40:59.706089Z

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 aaa3fac3-8f7a-452c-a3a7-10f0d67660de · 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 Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T23:49:45.254987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:49:45.254987Z digest=sha256:8cf2fd4ad7b1a2323d534a546ff8ea23eb7ce22dfcb8d01d40f2743d7fdd1ac7

Observation 85af8bd4-a4d9-4667-8b5c-42a18f74b032 · inbound

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models cites this paper.

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:40:59.778041Z

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=2026-08-07T11:40:36.102914Z digest=sha256:5808c798cbad4fc185284a12ae1843089e515fa414a30e7787e440d5c064e213