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Paper Citation Record · LEDGER

Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.14840.

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

pith.paper-citation-record.v1
2104.14840 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:46:12.771288Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T13:31:42.195525Z

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 7e205dc3-d351-4631-9e22-db78b72f9e64 · inbound

Towards Simple and Provable Parameter-Free Adaptive Gradient Methods cites this paper.

Towards Simple and Provable Parameter-Free Adaptive Gradient Methods Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T00:46:12.771288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:46:12.771288Z digest=sha256:ff07994d2028be0ceb26d28aa38be7d89c274383162e8fde90ed7fe861c42766

Observation b2700321-27a8-44be-bb10-b64b6f316864 · inbound

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models cites this paper.

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-08T13:31:42.202894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T13:31:42.112866Z digest=sha256:95af109ae86cfee62c1448e61d276ae48b417ad03a30b3ea85869e73155a340f