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Paper Citation Record · LEDGER

Recovering Plasticity of Neural Networks via Soft Weight Rescaling

As of 7 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 2026-08-07T06:34:17.273281+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

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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

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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

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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

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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

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source=pdf_text observed=2026-08-06T19:53:23.212007Z digest=sha256:1c9389edc8caeb902f032667136d5950d675876f174fb46fd6de4d3d1746655d

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

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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

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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 2026-08-07T06:34:17.273281+00:00.

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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

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source=pdf_text observed=2026-08-06T19:53:23.773747Z digest=sha256:ce65ea399c8d3094c081009b8f3f083aa7bc501442b50a1c5fdad60c35ab8aab

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

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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.

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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

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source=pdf_text observed=2026-08-06T19:53:24.140051Z digest=sha256:58980a6a11ab3d046cb9f2e65d46ce66e62e3aaed84f6bec46e4ee494032644a

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

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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

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source=pdf_text observed=2026-08-06T19:53:24.506723Z digest=sha256:7618ce139eb9bd2c7ce9c3b6c70d4cd3dcb9bd627d5554cb9c7de5e0ce6f8a1c

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

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source=pdf_text observed=2026-08-06T19:53:24.724233Z digest=sha256:87b44415790a47cb0f242672bb6672257cf6492dd8f6e8506b3c9e04fd600a62

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

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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

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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

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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.

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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

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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.

source=pdf_text observed=2026-08-06T19:53:22.839465Z digest=sha256:5f2a179eb8496b6a1355793ba0aeef78785a0ff3f9cf7882bdb37ead1adc5a9e

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

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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

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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

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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

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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

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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.

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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

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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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.