Paper Citation Record · LEDGER

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization

As of 17 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:1909.00182.

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

pith.paper-citation-record.v1
1909.00182 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T06:04:07.099376Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

26 of 26 outbound references displayed

verified exact0
verified fuzzy7
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 19bd6213-53ac-4e42-83a1-1aabcbddbed8 · outbound

This paper cites Layer Normalization.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Layer Normalization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:06.976026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f91df1e1-76ca-446a-84d2-b2a594e53831 · outbound

This paper cites PACT: Parameterized Clipping Activation for Quantized Neural Networks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:06.982430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0759882d-89fb-458a-ac88-0abcced25bbb · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Imagenet: A large-scale hierarchical image database

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:06.988171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4e3ab89-a548-4c48-81d2-bdd47b4a961f · outbound

This paper cites Generative adversarial nets.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Generative adversarial nets

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:06.993267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95b149b5-b3c6-475f-835b-dd3bd5bd421f · outbound

This paper cites Deep residual learning for image recognition.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Deep residual learning for image recognition

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:06.998324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a514a96a-d886-4203-a941-3c681b3b0a61 · outbound

This paper cites Bag of tricks for image classiﬁcation with convolutional neural networks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Bag of tricks for image classiﬁcation with convolutional neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.464499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ad262c59-a695-4fa4-8ebc-26044433f0dc · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Distilling the Knowledge in a Neural Network

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.008563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5fe11c-7e39-40e1-ae8c-4281ab3355d6 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.014411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d3980e-5265-4df6-939c-21d3b8939571 · outbound

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

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.019638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c0580cd-82d2-48fc-84b4-59b2329da2c9 · outbound

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

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.024575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 695633da-d319-4f93-a8ef-544fd20171ce · outbound

This paper cites The cifar-10 dataset.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization The cifar-10 dataset

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.448838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68508288-1f1a-4f9b-b7df-41c48ca3fec1 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural net- works.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Imagenet classiﬁcation with deep convolutional neural net- works

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.035180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 476dab1a-864c-47ce-8be1-5a2b2366dac4 · outbound

This paper cites Repr: Improved training of convolutional ﬁlters.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Repr: Improved training of convolutional ﬁlters

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.424376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05774e08-44b4-4213-ba64-162287a7237f · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.044597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74cf26cb-c1ca-44c2-b05f-135edae5908d · outbound

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

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.049394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1462646-85a2-4041-b834-2c766582911b · outbound

This paper cites Dropout: a simple way to prevent neural networks from overﬁtting.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Dropout: a simple way to prevent neural networks from overﬁtting

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.398477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8ee5865-1060-4c4e-8551-b7e44666c75f · outbound

This paper cites Going deeper with convolutions.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Going deeper with convolutions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.058389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d3ecf28-c3c6-4bef-9e73-082e4e2d80fd · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.062302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2d05cd5-8d55-48a1-9ef2-4e2a004314f8 · outbound

This paper cites Fixing the train-test resolution discrepancy.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Fixing the train-test resolution discrepancy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.066947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 711bb18b-ceb9-47e1-8d94-1911eb6e316f · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.071224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e2d9bf2-3ecc-448b-9787-f33509194f8b · outbound

This paper cites Regularization of neural networks using drop- connect.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Regularization of neural networks using drop- connect

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.371128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0607f61-7c88-41de-ba4b-c41c9fd53eb4 · outbound

This paper cites Towards dropout training for convolutional neural networks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Towards dropout training for convolutional neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.355672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7d3903df-b687-4f75-ba85-5dcf44e406d5 · outbound

This paper cites Group normalization.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Group normalization

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T06:04:07.339750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68f05454-3c53-4063-a32c-32d69eada630 · outbound

This paper cites Bag of Tricks for Image Classification with Convolutional Neural Networks.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Bag of Tricks for Image Classification with Convolutional Neural Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.089487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 424b3ff5-9bd5-40e6-8f88-b0b2aaa968fe · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization mixup: Beyond Empirical Risk Minimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.094451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1defcd17-782b-408c-ac12-b9370c8904fe · outbound

This paper cites Fixup Initialization: Residual Learning Without Normalization.

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization Fixup Initialization: Residual Learning Without Normalization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T06:04:07.099376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.