Paper Citation Record · LEDGER

AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.11215.

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

pith.paper-citation-record.v1
2402.11215 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:08:28.123888Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2928c122-0501-4787-9a67-f490766b7b7a · inbound

Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism cites this paper.

Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T23:08:28.123888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 437df03d-b11d-4460-a96d-ffa0d01fe23d · inbound

Efficient Training of Deep Networks using Guided Spectral Data Selection: A Step Toward Learning What You Need cites this paper.

Efficient Training of Deep Networks using Guided Spectral Data Selection: A Step Toward Learning What You Need AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:55:45.867498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d73c9710-d506-4114-b18f-8aad88581f0c · inbound

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models cites this paper.

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T16:36:50.522929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35e3f6af-612e-4efe-b773-e499fead9acf · inbound

COPUS: Co-adaptive Parallelism and Batch Size Selection in Large Language Model Training cites this paper.

COPUS: Co-adaptive Parallelism and Batch Size Selection in Large Language Model Training AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-09T03:55:07.660974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.