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Paper Citation Record · LEDGER

WNGrad: Learn the Learning Rate in Gradient Descent

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1803.02865.

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

pith.paper-citation-record.v1
1803.02865 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:44:07.620866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T12:28:07.393013Z

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 fce8ebf8-de76-4af6-adb5-88c91bea043c · inbound

prunAdag: an adaptive pruning-aware gradient method cites this paper.

prunAdag: an adaptive pruning-aware gradient method WNGrad: Learn the Learning Rate in Gradient Descent

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T05:44:07.620866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:44:07.620866Z digest=sha256:0922f9a872b1cc0fb332349d2908a7e9402824d95ac928d9dc1d3fc3315a5be9

Observation da049918-e738-43d5-8bbc-15a76c6ed5e2 · inbound

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo cites this paper.

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo WNGrad: Learn the Learning Rate in Gradient Descent

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:26:59.865849Z

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.

source=pdf_text observed=2026-05-10T07:19:59.335184Z digest=sha256:eeddb7d3da1102e75f33a4d0e8496d9da4ac7ba4cadbc81f902c7de6e95a238f

Observation 09ee4e5a-1fa8-4f94-8e12-79989842b1f8 · inbound

bAdag: an adaptive block coordinate gradient method for smooth nonconvex functions cites this paper.

bAdag: an adaptive block coordinate gradient method for smooth nonconvex functions WNGrad: Learn the Learning Rate in Gradient Descent

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-07-03T12:28:07.409844Z

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.

source=pdf_text observed=2026-06-27T09:00:34.960719Z digest=sha256:6be0e2d88ac07fa027c2bdce071b4d6712b4e7a886a0b6389df24fe42161c2b3