Paper Citation Record · LEDGER

Partial Channel Network: Compute Fewer, Perform Better

As of 15 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2502.01303.

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

pith.paper-citation-record.v1
2502.01303 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:49:53.634233Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T07:49:40.867148Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T01:14:27.453753Z

Reference resolution

43 of 43 outbound references displayed

verified exact0
verified fuzzy27
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81f3c7f5-4a75-45aa-a1c5-96b6eff62974 · outbound

This paper cites The kronecker product.

Partial Channel Network: Compute Fewer, Perform Better The kronecker product

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.485299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 89182a6c-0b1a-40e6-9260-df587e52e8b0 · outbound

This paper cites Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction.

Partial Channel Network: Compute Fewer, Perform Better Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.465916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 727943ba-3200-42bf-a130-fe02f2738b27 · outbound

This paper cites Run, don’t walk: Chasing higher flops for faster neural networks.

Partial Channel Network: Compute Fewer, Perform Better Run, don’t walk: Chasing higher flops for faster neural networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.446846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1dbe592b-c24d-496f-af73-f3fb1042dc95 · outbound

This paper cites Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1.

Partial Channel Network: Compute Fewer, Perform Better Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.421197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13712661-2a74-4655-a8c2-bb20213c2b78 · outbound

This paper cites Scaling up your kernels to 31x31: Revisiting large kernel design in cnns.

Partial Channel Network: Compute Fewer, Perform Better Scaling up your kernels to 31x31: Revisiting large kernel design in cnns

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.427153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 658a7699-3beb-458d-8636-4e6d316b5e18 · outbound

This paper cites Hawq: Hessian aware quantization of neural networks with mixed-precision.

Partial Channel Network: Compute Fewer, Perform Better Hawq: Hessian aware quantization of neural networks with mixed-precision

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.408123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bbe8110c-2bec-4e2c-b11d-37215275ca97 · outbound

This paper cites Single- and multi-gpu computing on nvidia- and amd-based server platforms for solidification modeling application.

Partial Channel Network: Compute Fewer, Perform Better Single- and multi-gpu computing on nvidia- and amd-based server platforms for solidification modeling application

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.389582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a88d08f9-ab13-4826-b028-c9dd9ff6b7f6 · outbound

This paper cites Ghostnet: More features from cheap operations.

Partial Channel Network: Compute Fewer, Perform Better Ghostnet: More features from cheap operations

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.371199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4c9fb508-22ba-4b16-b975-39e200977f41 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Partial Channel Network: Compute Fewer, Perform Better Deep Residual Learning for Image Recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.449139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d9914c8-cb15-4955-b1c4-624d1614b367 · outbound

This paper cites Mask r-cnn.

Partial Channel Network: Compute Fewer, Perform Better Mask r-cnn

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.454929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 195f38ce-5853-420b-bd88-30d3af515f7f · outbound

This paper cites Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition.

Partial Channel Network: Compute Fewer, Perform Better Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.460012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67b909b2-b403-4775-bafd-5be0979d2968 · outbound

This paper cites Searching for MobileNetV3.

Partial Channel Network: Compute Fewer, Perform Better Searching for MobileNetV3

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.465874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d31e7c38-b570-4f19-b79f-0db670f57ec8 · outbound

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

Partial Channel Network: Compute Fewer, Perform Better MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.471149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad21170-ed3a-4800-892b-d554a7485744 · outbound

This paper cites Squeeze-and-excitation net- works.

Partial Channel Network: Compute Fewer, Perform Better Squeeze-and-excitation net- works

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.337931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a7da57b6-9818-4861-87da-674a84447ac1 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.

Partial Channel Network: Compute Fewer, Perform Better Batch normalization: Accelerating deep network training by reducing internal co- variate shift

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.318860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2536722a-f091-48b7-8c33-fe06f8852d34 · outbound

This paper cites Programming mas- sively parallel processors: a hands-on approach.

Partial Channel Network: Compute Fewer, Perform Better Programming mas- sively parallel processors: a hands-on approach

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.300512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf33f261-da3d-43f3-b002-4a9515821949 · outbound

This paper cites Srm: A style-based recalibration module for convolutional neural networks.

Partial Channel Network: Compute Fewer, Perform Better Srm: A style-based recalibration module for convolutional neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.278399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ad87a2e3-38fc-4bf1-a47d-15566345ba04 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Partial Channel Network: Compute Fewer, Perform Better Swin transformer: Hierarchical vision transformer using shifted windows

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.255449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 91adaa80-8a3a-4628-a6fa-17ee11a52e81 · outbound

This paper cites A convnet for the 2020s.

Partial Channel Network: Compute Fewer, Perform Better A convnet for the 2020s

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.507388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5607f323-a45d-4997-b595-10625eddd9cb · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architec- ture design.

Partial Channel Network: Compute Fewer, Perform Better Shufflenet v2: Practical guidelines for efficient cnn architec- ture design

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.218380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9fd2719e-8a7e-46f0-a2fa-f3c08c7bcc7a · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

Partial Channel Network: Compute Fewer, Perform Better MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.517569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4efe5668-7c42-4b1a-a5df-d2f1acd50a84 · outbound

This paper cites Separable Self-attention for Mobile Vision Transformers.

Partial Channel Network: Compute Fewer, Perform Better Separable Self-attention for Mobile Vision Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.522971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16cc6d8c-4643-4db5-81ae-757bdd3e9d7b · outbound

This paper cites Edgevits: Competing light-weight cnns on mobile devices with vision transformers.

Partial Channel Network: Compute Fewer, Perform Better Edgevits: Competing light-weight cnns on mobile devices with vision transformers

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.198239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 75835875-4460-468b-a26e-b829969d84f6 · outbound

This paper cites Vision transformers are robust learners.

Partial Channel Network: Compute Fewer, Perform Better Vision transformers are robust learners

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.179614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6d8ab566-50a2-4823-bbf3-9316b29d6268 · outbound

This paper cites Do vision trans- formers see like convolutional neural networks? Advances in Neural Information Processing Systems, 34:12116–12128,.

Partial Channel Network: Compute Fewer, Perform Better Do vision trans- formers see like convolutional neural networks? Advances in Neural Information Processing Systems, 34:12116–12128,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.158354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 49b46897-2a37-4d17-96e9-f7f82690810b · outbound

This paper cites Hornet: Efficient high- order spatial interactions with recursive gated convolutions.

Partial Channel Network: Compute Fewer, Perform Better Hornet: Efficient high- order spatial interactions with recursive gated convolutions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.135487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ef401895-9688-4307-a71f-3c8adffb40f2 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Partial Channel Network: Compute Fewer, Perform Better Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.111174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 382cdd3f-8142-4f48-8b1f-d8214c916d16 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Partial Channel Network: Compute Fewer, Perform Better Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.554292Z

Source-reported events for the cited work

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Observation 66079d12-ddbd-4d88-aeaf-b025852c07a2 · outbound

This paper cites SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications.

Partial Channel Network: Compute Fewer, Perform Better SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.559625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33cede07-bcd6-418e-b7cd-de44e79ae507 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

Partial Channel Network: Compute Fewer, Perform Better Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.564982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64aa353b-92c5-4673-9799-11a2f23c270f · outbound

This paper cites Efficientnetv2: Smaller models and faster training.

Partial Channel Network: Compute Fewer, Perform Better Efficientnetv2: Smaller models and faster training

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.067387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 74dcfa27-59aa-4705-9305-c41bbbee195b · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Partial Channel Network: Compute Fewer, Perform Better Linformer: Self-Attention with Linear Complexity

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.576509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 526884ca-62ed-421b-ad4a-10b4848f115c · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions.

Partial Channel Network: Compute Fewer, Perform Better Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.048772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d54dd7c9-7d80-4807-8b47-102260207910 · outbound

This paper cites Cbam: Convolutional block attention module.

Partial Channel Network: Compute Fewer, Perform Better Cbam: Convolutional block attention module

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.027623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2ba88739-4010-4a7b-a824-b2e9795f1cd1 · outbound

This paper cites Rethinking and improving relative posi- tion encoding for vision transformer.

Partial Channel Network: Compute Fewer, Perform Better Rethinking and improving relative posi- tion encoding for vision transformer

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:54.007578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eb72910b-bf77-46b4-88eb-ee670f327bdc · outbound

This paper cites Aggregated residual transformations for deep neural networks.

Partial Channel Network: Compute Fewer, Perform Better Aggregated residual transformations for deep neural networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T15:49:53.597368Z

Source-reported events for the cited work

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Observation 13f6905c-7821-4f46-b15d-0d36309acbcc · outbound

This paper cites Focal modulation networks.

Partial Channel Network: Compute Fewer, Perform Better Focal modulation networks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:53.973670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a56f74e5-a86a-417c-96bc-c4ee2e84183f · outbound

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

Partial Channel Network: Compute Fewer, Perform Better Metaformer is actually what you need for vision

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:53.952973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a1fbb722-ffbf-4b5a-be48-b4a0986c1d69 · outbound

This paper cites Differ- entiable learning-to-group channels via groupable convolu- tional neural networks.

Partial Channel Network: Compute Fewer, Perform Better Differ- entiable learning-to-group channels via groupable convolu- tional neural networks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:53.933955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8df1e3d1-f13b-4243-8c3c-a1c6e4c2f7d1 · outbound

This paper cites • Firstly, we provide detailed explanations of our experi- mental setup, the specifics of the three PATConv blocks, and the different PartialNet variants.

Partial Channel Network: Compute Fewer, Perform Better • Firstly, we provide detailed explanations of our experi- mental setup, the specifics of the three PATConv blocks, and the different PartialNet variants

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:53.915091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c03d2dde-8a14-4bac-9d6f-0404bd6288da · outbound

This paper cites an unresolved cited work.

Partial Channel Network: Compute Fewer, Perform Better Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:49:53.896334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3d77cdab-43fc-4599-8f49-6c3dff1af346 · outbound

This paper cites For the full comparison of the classification task on the ImageNet-1k Benchmark, please refer to Tab.

Partial Channel Network: Compute Fewer, Perform Better For the full comparison of the classification task on the ImageNet-1k Benchmark, please refer to Tab

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:49:53.877990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d9fca5c7-6749-4565-a1be-b2f5138054f5 · outbound

This paper cites an unresolved cited work.

Partial Channel Network: Compute Fewer, Perform Better Unresolved cited work

Reference 43

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T15:49:53.856658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 8a660241-7354-4ab4-ad8b-d903839f09c8 · inbound

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection cites this paper.

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection Partial Channel Network: Compute Fewer, Perform Better

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T01:14:27.455094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 06758165-883a-4be3-a3a6-abede08687e1 · inbound

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection cites this paper.

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection Partial Channel Network: Compute Fewer, Perform Better

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T07:49:40.867148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.