Paper Citation Record · LEDGER

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1808.05671.

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

pith.paper-citation-record.v1
1808.05671 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:47:36.321431Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:18:56.227441Z

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 bccefbbd-be4d-4c98-8b61-1ba210c4253f · inbound

Adaptive Federated Optimization cites this paper.

Adaptive Federated Optimization On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 196

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:30:58.754320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08d1e229-8927-4b87-8566-90672bbda644 · inbound

Dual Averaging Converges for Nonconvex Smooth Stochastic Optimization cites this paper.

Dual Averaging Converges for Nonconvex Smooth Stochastic Optimization On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:36.321431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f164c29-be32-4d24-9a0b-52ed3180529c · inbound

LightSAM: Parameter-Agnostic Sharpness-Aware Minimization cites this paper.

LightSAM: Parameter-Agnostic Sharpness-Aware Minimization On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:32:07.720112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c234ca-22bf-4fd3-9933-f7575c503978 · inbound

Unified Scaling Laws for Compressed Representations cites this paper.

Unified Scaling Laws for Compressed Representations On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:11.956311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 450a164b-d7cd-4752-8a10-00037206b6d5 · inbound

AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates cites this paper.

AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:45.073914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3816d0f-3c14-4be1-a3be-b3d9ca3484b9 · inbound

On the Convergence of Muon and Beyond cites this paper.

On the Convergence of Muon and Beyond On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T15:56:34.125799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99e3d395-1878-45e9-9a30-e3f728ead727 · inbound

Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate cites this paper.

Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:16:00.264734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a3d186c-4a3d-418c-a054-8b6a9f3313a5 · inbound

Why Muon Outperforms Adam: A Curvature Perspective cites this paper.

Why Muon Outperforms Adam: A Curvature Perspective On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 200

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:06:44.983118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ec4e2980-1b78-422f-abd2-a03388884ca0 · inbound

Muon Learns More Robust and Transferable Features than Adam cites this paper.

Muon Learns More Robust and Transferable Features than Adam On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:27:30.171233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 932d527f-7689-4bfb-bd0d-c7d83dabc482 · inbound

MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization cites this paper.

MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:18:56.228895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b01ec68-af3b-433f-9650-6f3a773a9610 · inbound

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity cites this paper.

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Reference 94

Resolution: unresolved; no resolver link, observed 2026-07-12T00:07:55.485589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.