Paper Citation Record · LEDGER

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:2504.17243.

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

pith.paper-citation-record.v1
2504.17243 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:50:30.424836Z

measured 26 of 26 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T20:00:51.742281Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:45:39.714874Z

Reference resolution

24 of 24 outbound references displayed

verified exact1
verified fuzzy1
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ef8422a-c3ad-476c-8d7b-9340e0b62a94 · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Deep Learning using Rectified Linear Units (ReLU)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.320145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2894da2d-6228-4966-96fd-37d489dcf9c7 · outbound

This paper cites Unifying Grokking and Double Descent.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Unifying Grokking and Double Descent

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.325408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06225137-1a24-4b5e-8e9b-66396ee83cb4 · outbound

This paper cites The Complexity Dynamics of Grokking.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation The Complexity Dynamics of Grokking

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.330031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e5c19ef-2f63-4f62-9fe3-0a609da03048 · outbound

This paper cites Deep Grokking: Would Deep Neural Networks Generalize Better?.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Deep Grokking: Would Deep Neural Networks Generalize Better?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.334912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aababd0-630c-4d72-b746-3192979feaea · outbound

This paper cites Progress Measures for Grokking on Real-world Tasks.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Progress Measures for Grokking on Real-world Tasks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.339295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa3da2f4-7051-4f3e-87da-9aa1a844ae0c · outbound

This paper cites Train faster, generalize better: Stability of stochastic gradient descent.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Train faster, generalize better: Stability of stochastic gradient descent

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.344488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c82fdf55-bd8b-4930-9ab6-0fac3db285e4 · outbound

This paper cites Deep Networks Always Grok and Here is Why.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Deep Networks Always Grok and Here is Why

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.349783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2c56c2b-68dd-4af2-87e3-99b5ebbeb47c · outbound

This paper cites Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:50:30.599659Z

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.

Observation c4336675-f231-41b0-828a-f46151f1a563 · outbound

This paper cites A simple weight decay can improve generalization.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation A simple weight decay can improve generalization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.358731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f685c04-ee4a-42b6-a3cc-f94b14cec4cc · outbound

This paper cites Grokking as the Transition from Lazy to Rich Training Dynamics.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Grokking as the Transition from Lazy to Rich Training Dynamics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.362787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a37564-deed-4b6b-8aa2-e4482cc98c63 · outbound

This paper cites Grokfast: Accelerated Grokking by Amplifying Slow Gradients.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Grokfast: Accelerated Grokking by Amplifying Slow Gradients

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.367287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba54ceb-5796-4476-bdac-096df0429550 · outbound

This paper cites On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.371979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ecc05cc-2d49-4281-8a22-ac9c93a3be7a · outbound

This paper cites Towards Understanding Grokking: An Effective Theory of Representation Learning.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Towards Understanding Grokking: An Effective Theory of Representation Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.376358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d850ad7-a127-4649-9f90-863539939a91 · outbound

This paper cites Omnigrok: Grokking Beyond Algorithmic Data.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Omnigrok: Grokking Beyond Algorithmic Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.380861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b210549-0a7f-4c85-809d-6c93c51f74eb · outbound

This paper cites Do machine learning models memorize or generalize?, 2023.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Do machine learning models memorize or generalize?, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:30.743796Z

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.

Observation 9456e08e-8bf4-4118-84c1-b6ca1f69e603 · outbound

This paper cites Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.389414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95473366-ac30-4867-aca3-7b15c10b4c41 · outbound

This paper cites Grokking at the Edge of Numerical Stability.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Grokking at the Edge of Numerical Stability

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.393647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12990ba5-a444-4d69-a0f1-4c8376a8fab1 · outbound

This paper cites The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.397978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 002877d8-4953-4b1d-a9bd-f4ab0dc32264 · outbound

This paper cites Attention Is All You Need.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Attention Is All You Need

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.402216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ec34062-5c3e-4833-9ccf-a5b4b663d8bc · outbound

This paper cites On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.406554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7349a12-f4d1-4f4e-b089-69cc15ba1412 · outbound

This paper cites write newline.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation write newline

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.411104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d625316c-5a09-4820-aa67-c19e4b87901f · outbound

This paper cites @esa (Ref.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation @esa (Ref

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.416261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 978e9e9f-7b6b-4e60-b905-d7d0f7374fe4 · outbound

This paper cites an unresolved cited work.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:30.420705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eed8917-5811-4eac-8794-9f235b833cb6 · outbound

This paper cites an unresolved cited work.

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:50:30.704725Z

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.

Pith citing papers

Observation 5550eed6-9c28-46d4-bc14-04ed34d5e09f · inbound

Radial Suppression Accelerates Algorithmic Generalization: A Geometric Analysis of Delayed Generalization cites this paper.

Radial Suppression Accelerates Algorithmic Generalization: A Geometric Analysis of Delayed Generalization NeuralGrok: Accelerate Grokking by Neural Gradient Transformation

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:45:39.716270Z

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.

Observation 0194a570-693d-4131-8907-4b5885e01a2e · inbound

Structure-Specific Representational Priors Causally Control the Grokking Delay cites this paper.

Structure-Specific Representational Priors Causally Control the Grokking Delay NeuralGrok: Accelerate Grokking by Neural Gradient Transformation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T20:00:51.742281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.