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Paper Citation Record · LEDGER

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights

As of 20 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2501.09531.

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

pith.paper-citation-record.v1
2501.09531 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:00:37.973866Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

28 of 28 outbound references displayed

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External citation measurements

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Outbound references

Observation 3120c40f-0543-430b-abf5-d9713d315dc7 · outbound

This paper cites Xception: Deep learning with depthwise separable convo- lutions,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Xception: Deep learning with depthwise separable convo- lutions,

Reference 1

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Observation 48e738d2-323d-467a-8255-0f4e78542d28 · outbound

This paper cites Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 2

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Observation 3327e95b-39ae-4520-9976-c588cd75192a · outbound

This paper cites Learning both weights and connections for efficient neural networks,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Learning both weights and connections for efficient neural networks,

Reference 3

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Observation 8ddf2406-7390-4bbf-b012-b365efc1833b · outbound

This paper cites Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding,

Reference 4

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Observation f2f4e904-3789-4cee-873b-7bd3c9a69389 · outbound

This paper cites Scalable model compression by entropy penalized reparameterization,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Scalable model compression by entropy penalized reparameterization,

Reference 5

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Observation 14e3d028-6e7e-473a-81e1-3c0f818868ea · outbound

This paper cites Deep residual learning for image recognition,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Deep residual learning for image recognition,

Reference 6

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Observation 8e5d9d3a-647b-4962-87ea-4cd9ad4879ae · outbound

This paper cites Residual attention network for image classification,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Residual attention network for image classification,

Reference 7

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Observation bfa76204-2755-4269-b75f-f564cc9415d7 · outbound

This paper cites Squeeze-and-excitation networks,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Squeeze-and-excitation networks,

Reference 8

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Observation 641eee85-4096-4302-b2b7-0d90a6c178b7 · outbound

This paper cites Ternary Weight Networks.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Ternary Weight Networks

Reference 9

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Observation 7e94353c-1972-4ca5-9294-262f61af6a9b · outbound

This paper cites Linear symmetric quantization of neural networks for low-precision integer hardware,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Linear symmetric quantization of neural networks for low-precision integer hardware,

Reference 10

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Observation 825c2d97-cbae-4c62-9c8c-c43d819bea03 · outbound

This paper cites Learned step size quantization,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Learned step size quantization,

Reference 11

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Observation 2100aa14-ce37-4312-b722-c108462a53d2 · outbound

This paper cites Sifret, Rigid-Motion Scattering For Image Classification.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Sifret, Rigid-Motion Scattering For Image Classification

Reference 12

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Observation 2b0ff58b-9817-4ae9-84f9-fca9c56a4de4 · outbound

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

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 13

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Observation cec5d85f-767b-4c3c-ab0f-027473b16ccd · outbound

This paper cites Rethinking depthwise separable convolu- tions: How intra-kernel correlations lead to improved mobilenets,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Rethinking depthwise separable convolu- tions: How intra-kernel correlations lead to improved mobilenets,

Reference 14

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Observation 552ee54e-d335-4e7a-9493-20c9b2992dea · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Shufflenet: An extremely efficient convolutional neural network for mobile devices,

Reference 15

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Source-reported events for the cited work

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Observation 508ca271-fa6b-4c63-ad81-72c75f522092 · outbound

This paper cites Aggregated residual transformations for deep neural networks,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Aggregated residual transformations for deep neural networks,

Reference 16

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Observation 7694b1b9-b679-4e5a-9241-33dbed7142af · outbound

This paper cites Wolfram, A New Kind of Science.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Wolfram, A New Kind of Science

Reference 17

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Observation d50f4e2c-ec35-48bf-b51f-93eb78bc8db4 · outbound

This paper cites Chaotic cellular automaton for generating measure- ment matrix used in cs coding,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Chaotic cellular automaton for generating measure- ment matrix used in cs coding,

Reference 18

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Observation 86894e1c-e68f-490b-8a86-34f49edf026a · outbound

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MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Reservoir Computing using Cellular Automata

Reference 19

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Observation ec88d24d-79b6-4429-b85c-d1895ad5c5ef · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 20

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Observation 70a28515-fd87-48a5-be42-f7cd573b942f · outbound

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MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Binarized neural networks,

Reference 21

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Observation 7d6a9db4-6756-453d-9757-ee868e601070 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 22

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Observation b68a8a7a-ba0a-47c9-9399-a6446008e4a6 · outbound

This paper cites Cellpylib: A python library for working with cellular automata,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Cellpylib: A python library for working with cellular automata,

Reference 23

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Observation 9420a9ac-7e3c-4576-b10a-e0928f3f7349 · outbound

This paper cites Learning Multiple Layers of Features from Tiny Im- ages,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Learning Multiple Layers of Features from Tiny Im- ages,

Reference 24

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Observation 32dc3942-f763-4f2b-9199-f9cb77d354d9 · outbound

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MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Adam: A Method for Stochastic Optimization

Reference 25

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Observation 0c1e78f8-fa69-4839-9d5c-81f2cca8b896 · outbound

This paper cites Compressing deep convolutional neural networks by stacking low-dimensional binary convolution filters,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Compressing deep convolutional neural networks by stacking low-dimensional binary convolution filters,

Reference 26

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Observation 3607f234-1370-4ddf-925e-568a7f16761d · outbound

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MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 27

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Observation dd794cf0-3d2f-4cbe-beed-2e92d334f2ba · outbound

This paper cites Towards efficient tensor decomposition-based DNN model compression with optimization frame- work,.

MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights Towards efficient tensor decomposition-based DNN model compression with optimization frame- work,

Reference 28

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