Paper Citation Record · LEDGER

GradMax: Growing Neural Networks using Gradient Information

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2201.05125.

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

pith.paper-citation-record.v1
2201.05125 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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:43:59.233421Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T04:35:57.532084Z

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 52e060a5-2a58-4eef-be44-9a53f79c9a4e · inbound

Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence cites this paper.

Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence GradMax: Growing Neural Networks using Gradient Information

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:59.233421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5af9cb84-4daa-4cc5-9e3b-aa3b19fc1164 · inbound

Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts cites this paper.

Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts GradMax: Growing Neural Networks using Gradient Information

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:40:36.476897Z

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 c28fc6e0-50ac-4c69-a32e-2076e3f9913b · inbound

SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning cites this paper.

SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning GradMax: Growing Neural Networks using Gradient Information

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T05:27:09.807211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b250d378-4c49-4d5f-abcf-2d975b75b51a · inbound

An optimal control approach for neural network architecture adaptation with a posteriori error estimation cites this paper.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation GradMax: Growing Neural Networks using Gradient Information

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.533655Z

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.