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Paper Citation Record · LEDGER

Gradient Centralization: A New Optimization Technique for Deep Neural Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.01461.

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

pith.paper-citation-record.v1
2004.01461 v2

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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:41:54.687966Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-04T22:41:54.990404Z

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 ad8f8516-20c8-4289-a0bd-df23128b6690 · inbound

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions cites this paper.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Gradient Centralization: A New Optimization Technique for Deep Neural Networks

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-04T22:41:54.995964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-04T22:41:54.687966Z digest=sha256:4d59b60b35c76763e7c95b166a19e21b058c12943b2053c19b6dc3eacb5be523

Observation 3984f255-1259-4673-b55d-f8716771a73b · inbound

Hidden Boundary Motion in Transformer Optimization: Function-Space Orthogonalization of Affine Weight and Bias Updates cites this paper.

Hidden Boundary Motion in Transformer Optimization: Function-Space Orthogonalization of Affine Weight and Bias Updates Gradient Centralization: A New Optimization Technique for Deep Neural Networks

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T04:13:36.954559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:13:36.954559Z digest=sha256:ec2f311588d1b3d31f2c0e1a4934903abdb8153d6565444a8f77ad9f7b4f89e7