Paper Citation Record · LEDGER

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2507.09940.

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

pith.paper-citation-record.v1
2507.09940 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:48:04.945469Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

32 of 32 outbound references displayed

verified exact0
verified fuzzy22
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 76d6e3f8-6837-4691-895d-030c903fa038 · outbound

This paper cites Mazurowski.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Mazurowski

Reference 1

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Observation d7480a8d-f10e-47f2-9385-6cf75199e94c · outbound

This paper cites Provable benefits of overparameterization in model compression: From double descent to pruning neural networks.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Provable benefits of overparameterization in model compression: From double descent to pruning neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.420323Z

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Observation c81af38f-2aed-45cd-8b1d-b2e3bd65e9f1 · outbound

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Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Unresolved cited work

Reference 3

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Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Unresolved cited work

Reference 4

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Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Unresolved cited work

Reference 5

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Observation 555e1f35-f72f-411a-9599-de9391013a05 · outbound

This paper cites Belongie.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Belongie

Reference 6

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Observation 8392b0b4-4475-4375-ae6d-7f5d8359ebc9 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training An image is worth 16x16 words: Transformers for image recognition at scale

Reference 7

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Observation 41f4eca9-b1c6-43b7-bc21-c7665c9f6093 · outbound

This paper cites Gradmax: Grow- ing neural networks using gradient information.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Gradmax: Grow- ing neural networks using gradient information

Reference 8

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Observation 70a7d2b7-fbf6-490c-979d-3efc4d33dc92 · outbound

This paper cites Why random pruning is all we need to start sparse.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Why random pruning is all we need to start sparse

Reference 9

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Observation e857324e-ce10-4b07-a742-d8f498e8d49d · outbound

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Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Unresolved cited work

Reference 10

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Observation 0df6dc8f-383d-457d-b2a8-b5d8ba8f5431 · outbound

This paper cites Sharp: Sparsity and hidden activation re- play for neuro-inspired continual learning, 2023.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Sharp: Sparsity and hidden activation re- play for neuro-inspired continual learning, 2023

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.295358Z

Source-reported events for the cited work

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Observation 4d9864a8-e826-47b5-a70f-c73d9c5c2c78 · outbound

This paper cites Nice: Neurogenesis inspired con- textual encoding for replay-free class incremental learning.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Nice: Neurogenesis inspired con- textual encoding for replay-free class incremental learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.280758Z

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Observation 07d66099-92ef-4f5b-a112-25df748489dd · outbound

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Reference 13

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Observation f66ee1cd-0719-4677-ad49-a2b00530ad28 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification

Reference 14

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Observation 020dcebc-7f86-4b23-942d-562ef4a98439 · outbound

This paper cites Deep residual learning for image recognition.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Deep residual learning for image recognition

Reference 15

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This paper cites Van Horn, O.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Van Horn, O

Reference 16

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Observation b6b96cf2-bfab-4e15-8989-3d2b597afa0c · outbound

This paper cites Learning im- balanced datasets with maximum margin loss.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Learning im- balanced datasets with maximum margin loss

Reference 17

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Observation c491c42b-0062-4821-9b5d-22ec5345f98b · outbound

This paper cites Adaptive t-vmf dice loss: An effective expansion of dice loss for medical image segmen- tation.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Adaptive t-vmf dice loss: An effective expansion of dice loss for medical image segmen- tation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.198850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e8a9339-9424-4a91-a27e-07848e750628 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Pruning Filters for Efficient ConvNets

Reference 19

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Observation 317a45d5-0056-4dcd-ae9a-69be752dac3e · outbound

This paper cites Dynamic Model Pruning with Feedback.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Dynamic Model Pruning with Feedback

Reference 20

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Reference 21

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Observation e17b36f0-fa10-49f2-808f-ebc7a0587708 · outbound

This paper cites Very deep convolutional neural network based image classification using small train- ing sample size.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Very deep convolutional neural network based image classification using small train- ing sample size

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.167270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c0e3db15-0af3-4492-88d5-e11009b6a59a · outbound

This paper cites Large-scale long-tailed recognition in an open world.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Large-scale long-tailed recognition in an open world

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.152305Z

Source-reported events for the cited work

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Observation d5ae2df7-001c-4cc2-9ee0-dffac78561f9 · outbound

This paper cites Long-tail learning via logit adjustment, 2021.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Long-tail learning via logit adjustment, 2021

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.137778Z

Source-reported events for the cited work

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Observation 5bdde8c8-95f4-4480-81f0-06f08b35d921 · outbound

This paper cites Upscale: Un- constrained channel pruning.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Upscale: Un- constrained channel pruning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.122542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f116d041-5085-4e93-af04-8156acabf870 · outbound

This paper cites Learn- ing to grow pretrained models for efficient transformer train- ing.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Learn- ing to grow pretrained models for efficient transformer train- ing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.107316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2bcaa2a-6358-497d-b1d3-1d9d79a30e8f · outbound

This paper cites Firefly neural architecture descent: a general approach for growing neural networks.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Firefly neural architecture descent: a general approach for growing neural networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.091433Z

Source-reported events for the cited work

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Observation 3cf7ae2c-89f1-4a53-9fc1-69216e8a9abc · outbound

This paper cites Masked structural growth for 2x faster language model pre- training.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Masked structural growth for 2x faster language model pre- training

Reference 28

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Source-reported events for the cited work

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Observation c428aed2-fbf8-490e-b9ac-a7724b31b49c · outbound

This paper cites Mambaout: Do we really need mamba for vision? arXiv e-prints, pages arXiv–2405,.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Mambaout: Do we really need mamba for vision? arXiv e-prints, pages arXiv–2405,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.060793Z

Source-reported events for the cited work

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Observation ef2e7a7a-3c52-4684-89fe-733dce1baec6 · outbound

This paper cites Metaformer is actually what you need for vision, 2022.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Metaformer is actually what you need for vision, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.044600Z

Source-reported events for the cited work

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Observation c64d1d67-2d81-44dc-a599-c6bba7cca27d · outbound

This paper cites Yvinec, A.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Yvinec, A

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.026538Z

Source-reported events for the cited work

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Observation 003a8e59-1c53-4981-a73d-cfc69bf44b0d · outbound

This paper cites Zhang, K.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Zhang, K

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:05.011668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.