Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.13977.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T19:57:04.392443Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T00:47:29.870610Z
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 6e692353-883d-45f9-bdb6-35fc744601eb · inbound
Improved Online Confidence Bounds for Multinomial Logistic Bandits cites this paper.
Improved Online Confidence Bounds for Multinomial Logistic Bandits A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T19:57:04.392443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74d1f472-7316-4a57-b6e2-bf4905915cac · inbound
Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences cites this paper.
Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T20:36:00.471015Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ceae60ee-8341-4ea1-9555-cc8d3fb3a1b5 · inbound
Optimal Online and Offline Algorithms for Contextual MNL with Applications to Assortment and Pricing cites this paper.
Optimal Online and Offline Algorithms for Contextual MNL with Applications to Assortment and Pricing A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T12:56:20.047911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 756bf981-40ca-40d1-b884-f8358a708f67 · inbound
Best Arm Identification in Generalized Linear Bandits via Hybrid Feedback cites this paper.
Best Arm Identification in Generalized Linear Bandits via Hybrid Feedback A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T19:36:13.473382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e506c23f-81b8-483a-b3bf-fe6bef07ce70 · inbound
Algorithm for Contextual Queueing Bandits with Rate-Optimal Queue Length Regret cites this paper.
Algorithm for Contextual Queueing Bandits with Rate-Optimal Queue Length Regret A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:47:29.873100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.