Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Variance-Dependent Regret Lower Bounds for Contextual Bandits
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.12020.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T01:01:00.620439Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T00:17:29.395523Z
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 9a6934ba-2117-4b76-a2ac-30da7cef8825 · 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 Variance-Dependent Regret Lower Bounds for Contextual Bandits
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T01:01:00.620439Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f8c9e57e-7ff5-4d53-82b7-e440735d0e8a · inbound
Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts cites this paper.
Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts Variance-Dependent Regret Lower Bounds for Contextual Bandits
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:17:29.396809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 8f0583fd-3f28-4cf2-8839-16a45d85afa9 · inbound
Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set cites this paper.
Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set Variance-Dependent Regret Lower Bounds for Contextual Bandits
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T16:14:11.723269Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.