Paper Citation Record · LEDGER

Recovering Plasticity of Neural Networks via Soft Weight Rescaling

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2507.04683.

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

pith.paper-citation-record.v1
2507.04683 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:24.724233Z

measured 24 of 24 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact3
verified fuzzy4
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 28fda06e-1d20-47aa-90c0-feb775fe0246 · outbound

This paper cites The Impact of Reinitialization on Generalization in Convolutional Neural Networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling The Impact of Reinitialization on Generalization in Convolutional Neural Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.226802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1c0b7ed-1d60-4ec7-add1-bf86da7e46a3 · outbound

This paper cites an unresolved cited work.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:53:26.322323Z

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 f0c24a73-30f7-422c-a9f7-be1444faeef1 · outbound

This paper cites DSD: Dense-Sparse-Dense Training for Deep Neural Networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling DSD: Dense-Sparse-Dense Training for Deep Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.700857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4edfe33-53e8-4374-87f7-20dc05562855 · outbound

This paper cites Maintaining Plasticity in Continual Learning via Regenerative Regularization.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Maintaining Plasticity in Continual Learning via Regenerative Regularization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.120388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffd089dd-42eb-4230-bd46-73206291d18d · outbound

This paper cites Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.212007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d3c387a-767c-41c3-92e1-f5df125c9050 · outbound

This paper cites Normalization and effective learning rates in reinforcement learning.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Normalization and effective learning rates in reinforcement learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.365768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a252443-f1b9-4c2b-a098-a7476b4b9bb7 · outbound

This paper cites Step Out and Seek Around: On Warm-Start Training with Incremental Data.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Step Out and Seek Around: On Warm-Start Training with Incremental Data

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:53:25.326746Z

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 29e45db6-101b-4b58-831f-fed0fd73481e · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.773747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3f8a57d-f10a-47b5-ad4b-918103a765e3 · outbound

This paper cites Four Things Everyone Should Know to Improve Batch Normalization.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Four Things Everyone Should Know to Improve Batch Normalization

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:53:25.119201Z

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 b9bcc40b-f6c0-4bc1-8b42-283ffffc40c2 · outbound

This paper cites L2 Regularization versus Batch and Weight Normalization.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling L2 Regularization versus Batch and Weight Normalization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:24.140051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7853812f-a661-4740-9319-9e962a17a524 · outbound

This paper cites Spectral Norm Regularization for Improving the Generalizability of Deep Learning.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:24.361154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3438638d-716e-41b4-92e3-48c53cd8cab4 · outbound

This paper cites Three Mechanisms of Weight Decay Regularization.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Three Mechanisms of Weight Decay Regularization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:24.506723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45d489d3-7209-494e-bab8-440bbbe1795e · outbound

This paper cites CNN: We employed a Convolutional Neural Network (CNN), which is used in relatively small image classification.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling CNN: We employed a Convolutional Neural Network (CNN), which is used in relatively small image classification

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:26.085511Z

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 8b363a0a-09f7-4c51-aa25-2cee7c1c03fb · outbound

This paper cites Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning

Reference 1991

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.029630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d0f2ec-79f5-4145-b157-3ade2b71059c · outbound

This paper cites A study on the plasticity of neural networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling A study on the plasticity of neural networks

Reference 1996

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.571278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7818568-1e6c-4e45-8ac1-678a04179114 · outbound

This paper cites Layer-wise weight decay for deep neural networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Layer-wise weight decay for deep neural networks

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:27.060714Z

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 e71d85cf-99ba-47a0-acdd-0a711ab63358 · outbound

This paper cites Projection Based Weight Normalization for Deep Neural Networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Projection Based Weight Normalization for Deep Neural Networks

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:53:25.813746Z

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 5b36a974-61ab-4743-aaa9-e2264b80b0ad · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.897938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 832b8a69-2141-456c-bedd-4b675cc93be6 · outbound

This paper cites Weight Clipping for Deep Continual and Reinforcement Learning.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Weight Clipping for Deep Continual and Reinforcement Learning

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.641942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e146eb7-90a3-4fe3-bd34-a139f08d5bfa · outbound

This paper cites Layer Normalization.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Layer Normalization

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.474238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e4611f9-4d64-46e5-91c6-e5a7012d6064 · outbound

This paper cites Why Do We Need Weight Decay in Modern Deep Learning?.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Why Do We Need Weight Decay in Modern Deep Learning?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:22.327938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00899d96-c8d4-499f-a4da-b3a3a9636bcc · outbound

This paper cites Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks

Reference 2022

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:53:25.570536Z

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 6e7ce948-7aba-48a9-b729-c4f3716fc635 · outbound

This paper cites Understanding the disharmony between weight normaliza- tion family and weight decay.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Understanding the disharmony between weight normaliza- tion family and weight decay

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:26.802144Z

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 0075b811-cb36-454e-b187-7617537fe3a8 · outbound

This paper cites Dash: Warm-starting neural network training without loss of plasticity under stationarity.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Dash: Warm-starting neural network training without loss of plasticity under stationarity

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:26.543078Z

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

No inbound Pith citation observations are available.