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Paper Citation Record · LEDGER

Linear Contextual Bandits with Adversarial Corruptions

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.12615.

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

pith.paper-citation-record.v1
2110.12615 v1

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T22:03:14.905871Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T22:03:14.991772Z

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 fd60090a-87ca-4871-8e77-8ecfe6000492 · inbound

Multi-Agent Stochastic Bandits Robust to Adversarial Corruptions cites this paper.

Multi-Agent Stochastic Bandits Robust to Adversarial Corruptions Linear Contextual Bandits with Adversarial Corruptions

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-12T22:03:15.002790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-12T22:03:14.905871Z digest=sha256:c8863f16c674d6fbab11d04770c2e91b01d6268f0258751dae19e4ef2dd86754

Observation 6b825e82-aa31-46b7-b0c4-25ef54ff1b8c · inbound

A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions cites this paper.

A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions Linear Contextual Bandits with Adversarial Corruptions

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-03T01:01:06.395646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T01:01:06.395646Z digest=sha256:3056f3ea88c9f93f3c8117e7a204f18b690dd76da42da0667635d1791ccfea17