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Paper Citation Record · LEDGER

L2 Regularization versus Batch and Weight Normalization

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:1706.05350.

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

pith.paper-citation-record.v1
1706.05350 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:30:38.065681Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T20:30:07.604801Z

Reference resolution

0 of 0 outbound references displayed

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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 7a585054-2109-458c-a18c-f2af724084e3 · inbound

Progressive Growing of GANs for Improved Quality, Stability, and Variation cites this paper.

Progressive Growing of GANs for Improved Quality, Stability, and Variation L2 Regularization versus Batch and Weight Normalization

Reference 50

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verified exact
arxiv_id, observed 2026-05-12T12:24:03.451597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T12:24:03.252331Z digest=sha256:bdea23fec5d628686030d5920905fd53101210f748a8fe05fe7800dec24ed497

Observation 2fa8503a-3b0f-4b90-8015-d1ef96003f8c · inbound

Partition of Unity Physics-Informed Neural Networks (POU-PINNs): An Unsupervised Framework for Physics-Informed Domain Decomposition and Mixtures of Experts cites this paper.

Partition of Unity Physics-Informed Neural Networks (POU-PINNs): An Unsupervised Framework for Physics-Informed Domain Decomposition and Mixtures of Experts L2 Regularization versus Batch and Weight Normalization

Reference 39

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unresolved
no resolver link, observed 2026-08-11T20:30:38.065681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:30:38.065681Z digest=sha256:dbcb79861f2bf2aa66285458ce0421d7128b65dd4dec2593a59eeaf4f54da383

Observation 5f7fe79f-e44b-4e13-97d4-099f583cedd2 · inbound

Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study cites this paper.

Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study L2 Regularization versus Batch and Weight Normalization

Reference 36

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no resolver link, observed 2026-08-11T04:55:44.940599Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:55:44.940599Z digest=sha256:14a6a92350ffd62e90b5d8241fc0ba5febe6a2f8abc2ffade645f02fb607c7fa

Observation 7d11f847-52eb-4a65-8ff9-b9b72075da55 · inbound

GCSAM: Gradient Centralized Sharpness Aware Minimization cites this paper.

GCSAM: Gradient Centralized Sharpness Aware Minimization L2 Regularization versus Batch and Weight Normalization

Reference 44

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unresolved
no resolver link, observed 2026-08-10T18:10:11.484976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:10:11.484976Z digest=sha256:1fd6cc86463cba1c0903f4d549f83ca53e58576bde564e9b4489f4df1b97d1d1

Observation caed7d6c-b0b2-48a8-8a35-6c0e6eaba9a9 · inbound

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization cites this paper.

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization L2 Regularization versus Batch and Weight Normalization

Reference 43

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unresolved
no resolver link, observed 2026-08-08T12:32:20.137727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:32:20.137727Z digest=sha256:e5aca031996ccce7d54c92feee7396b3ca3f7c0fe2f1a762259c2b68c1cb4ae7

Observation 26c91935-1d70-4151-b8f3-0b46687b5b16 · inbound

Optimistic critics can empower small actors cites this paper.

Optimistic critics can empower small actors L2 Regularization versus Batch and Weight Normalization

Reference 52

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unresolved
no resolver link, observed 2026-08-07T11:55:37.396739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:55:37.396739Z digest=sha256:02ac555c2b521b41919b64c8c77d2ee4c428d8c7c45648ce0c975b0109807382

Observation 7c43b120-6677-4a8d-b09a-739151b93b4c · inbound

Why Gradients Rapidly Increase Near the End of Training cites this paper.

Why Gradients Rapidly Increase Near the End of Training L2 Regularization versus Batch and Weight Normalization

Reference 18

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no resolver link, observed 2026-08-07T11:32:04.103673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:32:04.103673Z digest=sha256:b5cec967b90f98b2dc6869a10b5fc4ff7f5d0df02c31300ff5ce6019a93285a7

Observation 2a60604b-da80-4266-9e95-f4c09912b31d · inbound

Scaling CrossQ with Weight Normalization cites this paper.

Scaling CrossQ with Weight Normalization L2 Regularization versus Batch and Weight Normalization

Reference 18

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unresolved
no resolver link, observed 2026-08-07T10:59:52.519682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:59:52.519682Z digest=sha256:434e2f24c5ccabc1657d0a820bff8a9ddb9f0ee28b87093c952252ea2e3173d3

Observation b9bcc40b-f6c0-4bc1-8b42-283ffffc40c2 · inbound

Recovering Plasticity of Neural Networks via Soft Weight Rescaling cites this paper.

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

Reference 20

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:53:24.140051Z digest=sha256:9530edc9b8cd05749cd77e2275b54164e42ef2efb3ba8a98bfc8ccca38329b16

Observation 27ce9aa4-7679-408c-a58c-ffa08a02f1c8 · inbound

How does the optimizer implicitly bias the model merging loss landscape? cites this paper.

How does the optimizer implicitly bias the model merging loss landscape? L2 Regularization versus Batch and Weight Normalization

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-18T09:51:13.434929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-18T09:49:41.550981Z digest=sha256:ed299c99f1911634e2d96b2036ea98c805a14a9d6e96adf3f6e1ad53eafc524e

Observation ee32b837-f833-465f-942a-c51f0a736f2a · inbound

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas? cites this paper.

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas? L2 Regularization versus Batch and Weight Normalization

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-17T23:32:13.115662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-17T23:31:56.523580Z digest=sha256:8d312e0eda7398cdd4bdfd6d7dca4b46d34b472c6c058b7f05318c9d89552543

Observation 87d17f04-756a-46d8-90bc-ac4ba13adf06 · inbound

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas? cites this paper.

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas? L2 Regularization versus Batch and Weight Normalization

Reference 6

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no resolver link, observed 2026-08-03T23:11:23.431555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:11:23.431555Z digest=sha256:51612c5c3d5f28adde84fda933f821aa7e9753204c8542f6b8b3574713a9a91a

Observation d08e855d-b896-4922-8c91-7ab2c1828371 · inbound

Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins cites this paper.

Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins L2 Regularization versus Batch and Weight Normalization

Reference 63

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verified exact
local_arxiv, observed 2026-05-16T22:08:36.110434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-16T22:05:59.007680Z digest=sha256:bf94e5574e4e49145e8d84d557d93d7185f2d2ed19cbddcf43c17fd9985ae8d6

Observation 02513f40-df82-426d-91b4-090120128424 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control L2 Regularization versus Batch and Weight Normalization

Reference 88

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verified exact
arxiv_id, observed 2026-05-10T22:15:49.748208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T20:04:56.512544Z digest=sha256:b552701bbe7866de1410f584d1cfc0ad57c267fe642ee8bf3544ede723477f46

Observation 71b456e0-81ca-4f1f-81da-1b9948b66095 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control L2 Regularization versus Batch and Weight Normalization

Reference 88

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verified exact
local_arxiv, observed 2026-05-19T17:12:41.333270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T17:08:31.770889Z digest=sha256:58bf73cd5a83870e22b115e91c18b288d6eef7a7e32edb1bede955f28d2e2367

Observation c3b19d22-fe57-4575-98a6-09ad5fcf953d · inbound

Adaptive Norm-Based Regularization for Neural Networks cites this paper.

Adaptive Norm-Based Regularization for Neural Networks L2 Regularization versus Batch and Weight Normalization

Reference 20

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metadata mismatch
arxiv_id, observed 2026-05-11T15:16:08.528046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-09T20:23:29.004886Z digest=sha256:2211ee5317df56e74b35fc527855a1cffe12b11a0798f32935611f24b9bbe0f5

Observation dec1ef61-f772-48cb-bf0d-2377857ca165 · inbound

Demystifying Manifold Constraints in LLM Pre-training cites this paper.

Demystifying Manifold Constraints in LLM Pre-training L2 Regularization versus Batch and Weight Normalization

Reference 60

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verified exact
arxiv_id, observed 2026-05-11T17:16:08.747351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T17:44:44.438637Z digest=sha256:5f9c4c21b872ef7bae42727410e3cd8c128adbd41bd3bb8b27dbbc3db5f04f6e

Observation 8c7fd5da-bed8-445a-9099-2236dfe6b64b · inbound

XQCfD: Accelerating Fast Actor-Critic Algorithms with Prior Data and Prior Policies cites this paper.

XQCfD: Accelerating Fast Actor-Critic Algorithms with Prior Data and Prior Policies L2 Regularization versus Batch and Weight Normalization

Reference 40

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verified exact
arxiv_id, observed 2026-05-12T05:46:30.582762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T04:57:30.301209Z digest=sha256:b751d49831faa9bc6d180ea1e75ad99541f4045af266b0e12f37460fd3024bbf

Observation c7995a45-334c-4ac4-acbe-5340ca7df28d · inbound

Does Weight Decay Enhance Training Stability? cites this paper.

Does Weight Decay Enhance Training Stability? L2 Regularization versus Batch and Weight Normalization

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-05-20T19:53:42.917608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-20T19:49:01.351717Z digest=sha256:5c58226e658d3ae89a794180cd2985068c75ca664407877b26c29a12bf35ca8a

Observation f46ce5b8-436a-48c6-87d8-5c8dfaa162c9 · inbound

ScheduleFree+: Scaling Learning-Rate-Free & Schedule-Free Learning to Large Language Models cites this paper.

ScheduleFree+: Scaling Learning-Rate-Free & Schedule-Free Learning to Large Language Models L2 Regularization versus Batch and Weight Normalization

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-20T12:23:16.778398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-20T12:22:30.263086Z digest=sha256:3e46cdadd99dd6b2f682e12dac9bfa903b2c75041cc7d47b0bae747b4f433238

Observation e2df2b38-aae1-4530-962d-b1c83bf6e800 · inbound

Anytime Training with Schedule-Free Spectral Optimization cites this paper.

Anytime Training with Schedule-Free Spectral Optimization L2 Regularization versus Batch and Weight Normalization

Reference 74

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verified exact
local_arxiv, observed 2026-05-25T05:40:24.369953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T05:38:16.958574Z digest=sha256:ed996404675038958f4977de9d6e2266ad0b2eb289d24b114cbb3637736379af

Observation 9483aa39-d6f4-4b96-be52-8b3dac4aaaf7 · inbound

Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability cites this paper.

Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability L2 Regularization versus Batch and Weight Normalization

Reference 75

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metadata mismatch
local_arxiv, observed 2026-07-02T06:16:43.886355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-28T07:26:25.407267Z digest=sha256:388c570da20774ec6a7409d067a9d3f9530091f39d6850d57531bedfd3bbbc79

Observation 33e39d97-a77e-4dbb-a2c1-e612861f3c7d · inbound

Preserving Plasticity in Continual Learning via Dynamical Isometry cites this paper.

Preserving Plasticity in Continual Learning via Dynamical Isometry L2 Regularization versus Batch and Weight Normalization

Reference 15

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verified exact
local_arxiv, observed 2026-07-03T00:07:28.498369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T17:26:20.769515Z digest=sha256:964e929e4cbf0602d003d0f67361048004e274712bd4b64f869b1985a3658135

Observation 5d5e9f3e-be8a-4ed4-8584-e3fa79351c9e · inbound

Weibull Weight-Scale Parameter Evolution under AdamW Training Dynamics cites this paper.

Weibull Weight-Scale Parameter Evolution under AdamW Training Dynamics L2 Regularization versus Batch and Weight Normalization

Reference 17

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local_arxiv, observed 2026-07-03T13:48:20.868063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-27T07:34:04.456453Z digest=sha256:a160c20fe863d6f24fd8e66b70229a01e5d44d0891cd9b6c9bbe626ee240e88f

Observation 404bda4e-ab3e-485c-b0ac-da7ea12497b4 · inbound

Muown Implicitly Performs Angular Step-size Decay cites this paper.

Muown Implicitly Performs Angular Step-size Decay L2 Regularization versus Batch and Weight Normalization

Reference 1

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metadata mismatch
local_arxiv, observed 2026-07-04T10:49:45.667240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-26T08:32:35.411051Z digest=sha256:e31b5f6c6dbcb5c42692369f6c3c9353d8fa23b8854ae6221e98951d465f7ad7

Observation 6082929f-81bd-4e0f-9e40-7dad3d69d83d · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors L2 Regularization versus Batch and Weight Normalization

Reference 75

Resolution
verified exact
local_arxiv, observed 2026-07-04T20:30:07.606260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-25T20:05:09.179627Z digest=sha256:02c182c9a4c9977bf628d81b826501e270022d658468daff052a4bdde865a501

Observation f474a6f3-a46d-4b06-9181-e3ec6d075c80 · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors L2 Regularization versus Batch and Weight Normalization

Reference 75

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unresolved
no resolver link, observed 2026-08-02T10:14:11.556096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T10:14:11.556096Z digest=sha256:a8d30c5ca51dbc810960ce232526e00233a9e907ea0169cd55d1a2bb0bb12935

Observation 1b0bb89b-2852-45b5-8e8c-2359a173e3d5 · inbound

On the Nonlinearity of Learning Rate Scaling for LLM Training cites this paper.

On the Nonlinearity of Learning Rate Scaling for LLM Training L2 Regularization versus Batch and Weight Normalization

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-06-30T08:24:26.807479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T08:15:20.191222Z digest=sha256:91f79e4b92002fe1740b48b65dc4b606aaf7da4f92724b40001423d9d0d81ee8

Observation 6d64212f-a37d-4399-90c7-f7c594462439 · inbound

Dead-Direction Conditioners: Gauge-Equivariant Preconditioning for Deep Networks cites this paper.

Dead-Direction Conditioners: Gauge-Equivariant Preconditioning for Deep Networks L2 Regularization versus Batch and Weight Normalization

Reference 33

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verified exact
local_arxiv, observed 2026-06-30T08:04:28.130994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-30T07:58:57.890346Z digest=sha256:0fc654663a9c585123644d5da37311dcee37780f7a5487ba210b8ca800652b3a

Observation 3c50d069-29ae-49bd-9ff6-db04e345740e · inbound

Weight-norm Criticality: A Mechanism for Loss Spikes Induced by the Normalization and Weight Decay cites this paper.

Weight-norm Criticality: A Mechanism for Loss Spikes Induced by the Normalization and Weight Decay L2 Regularization versus Batch and Weight Normalization

Reference 1

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unresolved
no resolver link, observed 2026-08-01T08:50:40.509350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:50:40.509350Z digest=sha256:33a2a4fce4e5b627ef68152302ad1a84e7cd1e05f9a24a70f31c7e1b4e8899c9

Observation c37093d2-1cc2-4b7c-88e6-2b19a53ca26f · inbound

Hyperball May Not Be a Free Lunch cites this paper.

Hyperball May Not Be a Free Lunch L2 Regularization versus Batch and Weight Normalization

Reference 12

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no resolver link, observed 2026-08-01T04:48:13.221193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:48:13.221193Z digest=sha256:7625b3945a459c9874ddd684c3356fddd938455a3d99d9a5f116f2c41c260a2b

Observation b4c0e474-cbe7-43f0-8789-3ee316ab8a79 · inbound

Scale Weight Decay and Train Better cites this paper.

Scale Weight Decay and Train Better L2 Regularization versus Batch and Weight Normalization

Reference 45

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no resolver link, observed 2026-07-30T12:53:41.060313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:53:41.060313Z digest=sha256:2b9639167913ab7aa06b2a7aabf0ad1fda1216a4896d8fd165dfe35e2c16a2d3