Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adaptive Learning Rates for Faster Stochastic Gradient Methods
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2208.05287.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T13:53:06.068984Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T19:03:21.942936Z
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 5adb17da-ad5a-46da-b5b3-05ffdbf10a0e · inbound
Tighter Performance Theory of FedExProx cites this paper.
Tighter Performance Theory of FedExProx Adaptive Learning Rates for Faster Stochastic Gradient Methods
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:03:21.946282Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 47b95590-d0b5-4e95-b70d-e18acadf2c7a · inbound
The Ball-Proximal (="Broximal") Point Method: a New Algorithm, Convergence Theory, and Applications cites this paper.
The Ball-Proximal (="Broximal") Point Method: a New Algorithm, Convergence Theory, and Applications Adaptive Learning Rates for Faster Stochastic Gradient Methods
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T13:53:06.068984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32766695-93b6-4213-8436-5fe17a3bdafd · inbound
Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients cites this paper.
Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients Adaptive Learning Rates for Faster Stochastic Gradient Methods
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T19:10:48.546822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.