Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Revisiting Convergence of AdaGrad with Relaxed Assumptions
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.13794.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T00:23:05.225264Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T21:05:46.760315Z
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 ee49d851-ff89-406e-a56a-2afb4caed0c7 · inbound
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping cites this paper.
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping Revisiting Convergence of AdaGrad with Relaxed Assumptions
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:23:05.225264Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5617da72-3a8e-4f61-b62c-5cda2d5d9077 · inbound
Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks cites this paper.
Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks Revisiting Convergence of AdaGrad with Relaxed Assumptions
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T20:46:05.467029Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9be26feb-79ba-4624-a794-d45fe06393f6 · inbound
On MUON optimization: From non-convergence to an error analysis with Polar Express and the Newton-Schulz polynomial from implementations cites this paper.
On MUON optimization: From non-convergence to an error analysis with Polar Express and the Newton-Schulz polynomial from implementations Revisiting Convergence of AdaGrad with Relaxed Assumptions
Reference 75
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T21:05:46.763234Z
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.