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Paper Citation Record · LEDGER

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning

As of 7 August 2026, this Paper Citation Record lists 100 of 182 outbound references and 0 inbound Pith citation observations for arXiv:2507.19795.

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

pith.paper-citation-record.v1
2507.19795 v1

Coverage vector

measured 100 of 182 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:06:51.147174Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

100 of 182 outbound references displayed

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  • verified fuzzy0
  • unresolved100
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  • malformed identifier0
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Outbound references

Observation 070c60c3-5d12-491b-9f6c-e83e702dd58f · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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Observation a759c726-2c8d-4e10-8f58-ebadc4394e3a · outbound

This paper cites Dbpedia: A nucleus for a web of open data.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Dbpedia: A nucleus for a web of open data

Reference 2

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Observation 6c0ac0c8-8591-41fb-96bb-39f89a606437 · outbound

This paper cites Neural machine translation by jointly learning to align and translate, 2016.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Neural machine translation by jointly learning to align and translate, 2016

Reference 3

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Observation 089fca25-278d-4ce5-a8b0-bbc58350984d · outbound

This paper cites Distilling the knowledge from conditional normalizing flows.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Distilling the knowledge from conditional normalizing flows

Reference 4

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Observation ec860435-881d-4b73-96f4-c89e0b03798b · outbound

This paper cites Semantic photo manipulation with a generative image prior.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Semantic photo manipulation with a generative image prior

Reference 5

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Observation 7bd85612-fb82-49a4-b209-616fdea7f9e8 · outbound

This paper cites an unresolved cited work.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unresolved cited work

Reference 6

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Observation 1a147371-7cbd-4c61-8baa-4ef2a26f1f0d · outbound

This paper cites Longformer: The Long-Document Transformer.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Longformer: The Long-Document Transformer

Reference 7

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Observation b09a2656-3a25-493b-bad9-05d54049a079 · outbound

This paper cites Sylvester Normalizing Flows for Variational Inference.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Sylvester Normalizing Flows for Variational Inference

Reference 8

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Observation d23f6cdf-ca66-4839-b6b7-e54635233acb · outbound

This paper cites Unleashing transformers: Parallel token prediction with discrete absorbing diffusion for fast high-resolution image generation from vector-quantized codes.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unleashing transformers: Parallel token prediction with discrete absorbing diffusion for fast high-resolution image generation from vector-quantized codes

Reference 9

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Observation e1a9daa0-2d9e-4549-8363-ebefb4a1729d · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unresolved cited work

Reference 10

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Observation be09bf4a-29de-485b-82f0-4035df11f923 · outbound

This paper cites Model compression.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Model compression

Reference 11

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Observation 793d2b1d-683f-483c-9e7c-9c15c5782389 · outbound

This paper cites Proxylessnas: Direct neural architecture search on target task and hardware.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Proxylessnas: Direct neural architecture search on target task and hardware

Reference 12

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Observation a1895085-fd07-4ccd-94fe-43f42a7465f5 · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Cascade r-cnn: Delving into high quality object detection

Reference 13

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Observation 648918c6-b4d4-4d93-8a5d-c85f7e183672 · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unresolved cited work

Reference 14

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Observation 7df8bb55-940e-47a9-b346-2bc0ab49f12d · outbound

This paper cites Residual Flows for Invertible Generative Modeling.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Residual Flows for Invertible Generative Modeling

Reference 15

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Observation 9a1682e7-47c9-420c-9f35-1c34f167d119 · outbound

This paper cites On the relationship between self-attention and convolutional layers.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning On the relationship between self-attention and convolutional layers

Reference 16

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Observation 8c4a8b1f-a3e8-4641-a9aa-ff205bec0056 · outbound

This paper cites Scalable high-resolution pixel-space image synthesis with hourglass diffusion transformers.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Scalable high-resolution pixel-space image synthesis with hourglass diffusion transformers

Reference 17

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Observation a41f28e4-da3e-4bf5-8475-09ea1fb42f2f · outbound

This paper cites Approximation with artificial neural networks.Faculty of Sciences, Etvs Lornd University, Hungary , 24(48):7, 2001.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Approximation with artificial neural networks.Faculty of Sciences, Etvs Lornd University, Hungary , 24(48):7, 2001

Reference 18

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Observation e9ee7828-92c1-4ae1-9230-5ec823e32374 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Randaugment: Practical automated data augmentation with a reduced search space

Reference 19

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Observation 1377b4c8-5e6f-4294-a304-ee8998b1ec70 · outbound

This paper cites Flow Matching in Latent Space.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Flow Matching in Latent Space

Reference 20

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Observation 4276fdd8-b0ca-48b1-a64d-9df14e2d5321 · outbound

This paper cites Flashattention-2: Faster attention with better parallelism and work partitioning.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Flashattention-2: Faster attention with better parallelism and work partitioning

Reference 21

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Observation 93270ccd-e48d-4eb7-b9a8-9b70c4876cf7 · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 22

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Observation 5474901a-2ac5-495f-9ee7-d739c862d9db · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Imagenet: A large-scale hierarchical image database

Reference 23

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Observation f368c111-dd35-4f9f-89b1-20d09b229c8e · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 24

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Observation 06d97509-c12a-455d-8b0f-1ce73856a2a9 · outbound

This paper cites Ensemble methods in machine learning.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Ensemble methods in machine learning

Reference 25

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Observation c3b2a7ae-134e-4616-b343-25314c3569d8 · outbound

This paper cites Density estimation using real nvp, 2017.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Density estimation using real nvp, 2017

Reference 26

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Observation 906ab785-7c60-4d47-bb7b-2fa3549beab9 · outbound

This paper cites Invertible Generative Modeling using Linear Rational Splines.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Invertible Generative Modeling using Linear Rational Splines

Reference 27

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Observation dda88302-748c-4afa-9a39-c7b899fd8ff1 · outbound

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

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 28

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Observation 5bfa5ba9-729b-4fad-9612-b6b269492633 · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Augmented Neural ODEs

Reference 29

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Observation 77439084-6c1d-4a41-81c4-f23f778dba6a · outbound

This paper cites Cubic-Spline Flows.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Cubic-Spline Flows

Reference 30

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Observation 28b67fa9-d277-431e-9ee7-6d37db9250d9 · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Softmax linear units

Reference 31

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Observation 2aa7e9b5-deb8-464f-a6ec-053bd6ee0813 · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Visualizing higher-layer features of a deep network, 2009

Reference 32

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Observation 666fe322-2a35-4355-862e-ae439a8a9f86 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 33

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Observation ff0831d4-cb96-423a-bfc3-0c6018b91b3c · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Fuhr and Michael Kallay

Reference 34

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Observation dc64602e-a2de-44c8-a48c-a3a496f7e955 · outbound

This paper cites A new algorithm for data compression.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning A new algorithm for data compression

Reference 35

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Observation 58fc5889-3e95-47d1-b36d-44e19b67a47f · outbound

This paper cites Swagan: A style-based wavelet-driven generative model.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Swagan: A style-based wavelet-driven generative model

Reference 36

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Observation 78168745-2ac9-467d-9653-c95141ecf360 · outbound

This paper cites Masked diffusion transformer is a strong image synthesizer.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Masked diffusion transformer is a strong image synthesizer

Reference 37

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Observation e756e0c4-60ea-4537-87d2-27cfe4c59a27 · outbound

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Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Mahoney, and Kurt Keutzer

Reference 38

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Observation 3c095272-db90-47a7-a99e-ff43dbfc3b74 · outbound

This paper cites Ganalyze: Toward visual definitions of cognitive image properties.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Ganalyze: Toward visual definitions of cognitive image properties

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Observation 8df19ef3-b00f-491d-8261-3a96665861d2 · outbound

This paper cites Deep Learning.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Deep Learning

Reference 40

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Observation a23db819-178f-43a7-96eb-e04805a27d0a · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde- Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde- Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

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Observation e2644c66-f890-4554-a1bf-05d458044f9e · outbound

This paper cites an unresolved cited work.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unresolved cited work

Reference 42

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Observation 34a3f24b-6fc6-44f9-aed6-cc7ca9e3b1e5 · outbound

This paper cites Neural turing machines, 2014.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Neural turing machines, 2014

Reference 43

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Observation a7490690-3c38-48cc-b00b-16f999bcdea2 · outbound

This paper cites Densely connected normalizing flows, 2021.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Densely connected normalizing flows, 2021

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Observation fc805aa6-caa6-4b0b-9e3e-67a2a54ddf62 · outbound

This paper cites Pattern theory: from representation to inference.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Pattern theory: from representation to inference

Reference 45

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Observation 7b110edc-1df4-404a-9d97-13af0ac58142 · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces, 2024.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Mamba: Linear-time sequence modeling with selective state spaces, 2024

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Observation e90ddf50-d7c0-4589-8ee7-55fa0168dae3 · outbound

This paper cites Starflow: Scaling latent normalizing flows for high-resolution image synthesis, 2025.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Starflow: Scaling latent normalizing flows for high-resolution image synthesis, 2025

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Observation 53203af2-21cc-4ec3-a879-e31a22b3b649 · outbound

This paper cites Variational Inference with Orthogonal Normalizing Flows.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Variational Inference with Orthogonal Normalizing Flows

Reference 48

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Observation ae446254-25c6-4a3c-b0bf-6220bf1cca74 · outbound

This paper cites Neighborhood attention: Dynamic restriction of self-attention, 2023.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Neighborhood attention: Dynamic restriction of self-attention, 2023

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Observation 135e01b6-f517-474a-bb6e-b2ffe06b7e23 · outbound

This paper cites Dilated neighborhood attention transformer, 2023.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Dilated neighborhood attention transformer, 2023

Reference 50

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Observation d17944df-d8ef-4c80-93f6-a45ffaa1f9c7 · outbound

This paper cites Escaping the big data paradigm with compact transformers, 2022.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Escaping the big data paradigm with compact transformers, 2022

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Observation bf6873b2-9d89-42d1-bf6a-711f2ec1323a · outbound

This paper cites Neighborhood attention transformer.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Neighborhood attention transformer

Reference 52

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Observation c0511483-1d93-4508-839c-866a1922277c · outbound

This paper cites Faster neighborhood attention: Reducing the O(n2) cost of self attention at the threadblock level, 2024.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Faster neighborhood attention: Reducing the O(n2) cost of self attention at the threadblock level, 2024

Reference 53

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Observation a8d0a652-8582-4b5b-a032-8089200028b7 · outbound

This paper cites Generalized neighborhood attention: Multi-dimensional sparse attention at the speed of light, 2025.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Generalized neighborhood attention: Multi-dimensional sparse attention at the speed of light, 2025

Reference 54

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Observation 556311bd-ba03-47d9-9648-2e3006018c86 · outbound

This paper cites Deep residual learning for image recognition.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Deep residual learning for image recognition

Reference 55

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Observation 0a62a550-7e7d-4e1a-b71f-2d2b87ed7ae2 · outbound

This paper cites Deep residual learning for image recognition.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Deep residual learning for image recognition

Reference 56

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Observation 73f9795b-119f-400a-bc37-8ba359cd43fe · outbound

This paper cites Identity mappings in deep residual networks.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Identity mappings in deep residual networks

Reference 57

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Observation a6e67e72-709f-49b2-be4c-63d62ef604cb · outbound

This paper cites Mask r-cnn.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Mask r-cnn

Reference 58

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Observation f594c7c4-00b7-40ad-96b7-da9bd77c1c62 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Masked autoencoders are scalable vision learners

Reference 59

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Observation 559425f9-1543-42bb-97e0-4f238b670c78 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 60

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Observation 54af68a6-e965-4e7a-98fa-ea7b2f8d2726 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Distilling the Knowledge in a Neural Network

Reference 61

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Observation 792e3bff-b308-4942-9dc8-0032bf719ca5 · outbound

This paper cites an unresolved cited work.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Unresolved cited work

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Observation 458c721f-6732-4dc3-a7d8-b645aee38e67 · outbound

This paper cites Denoising diffusion probabilistic models.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Denoising diffusion probabilistic models

Reference 63

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Observation 87162926-f4e5-4d78-8c67-ce0c938c78af · outbound

This paper cites The convolution exponential and generalized sylvester flows.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning The convolution exponential and generalized sylvester flows

Reference 64

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Observation 1dd434c3-6241-4ef1-ace8-1d2a471e8245 · outbound

This paper cites Simple diffusion: End-to- end diffusion for high resolution images, 2023.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Simple diffusion: End-to- end diffusion for high resolution images, 2023

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Observation 6e35e3dc-80fe-4749-a876-553ed8061a45 · outbound

This paper cites On the limitations of compute thresholds as a governance strategy, 2024.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning On the limitations of compute thresholds as a governance strategy, 2024

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Observation 09181edf-e9d4-45bd-9e06-adfec0f098ed · outbound

This paper cites Multilayer feedforward networks are universal approximators.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Multilayer feedforward networks are universal approximators

Reference 67

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Observation 273ad117-c694-4237-8a69-9902371222da · outbound

This paper cites Local relation networks for image recognition.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Local relation networks for image recognition

Reference 68

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Observation 3bd1a13c-0cde-4b96-b40f-5b201fb2d4f8 · outbound

This paper cites Squeeze-and-excitation networks.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Squeeze-and-excitation networks

Reference 69

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Observation e982c090-a566-410b-ad1f-5c19b26715fe · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Arbitrary style transfer in real-time with adaptive instance normalization

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Observation 2dd1e4fc-89a7-4dfb-ae81-19dbfabed34e · outbound

This paper cites Lawrence Zitnick.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Lawrence Zitnick

Reference 71

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Observation b7b46247-25b2-43e1-ba0c-ab7668f749a5 · outbound

This paper cites Lawrence Zitnick.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Lawrence Zitnick

Reference 72

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Observation 1800086c-2857-4384-b083-9d2aadb9dba0 · outbound

This paper cites Estimation of Non-Normalized Statistical Models by Score Matching.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Estimation of Non-Normalized Statistical Models by Score Matching

Reference 73

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Observation cea953da-668c-4175-9c08-c80ab35235d1 · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Averaging Weights Leads to Wider Optima and Better Generalization

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Observation 44b46676-4c5a-4f68-b646-af0900b4e165 · outbound

This paper cites Oneformer: One transformer to rule universal image segmentation.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Oneformer: One transformer to rule universal image segmentation

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Observation 22c222e9-8c81-42aa-9043-fc9410cc51e5 · outbound

This paper cites Semask: Semantically masked transformers for semantic segmentation.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Semask: Semantically masked transformers for semantic segmentation

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Observation c56ffce9-3be8-445d-b81a-23745962c277 · outbound

This paper cites Face Perception, chapter 43.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Face Perception, chapter 43

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Observation c37d5d5e-056f-4cb1-a791-fb3e7ba5b540 · outbound

This paper cites Progressive growing of GANs for improved quality, stability, and variation.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Progressive growing of GANs for improved quality, stability, and variation

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Observation e65740ff-2e8f-4305-b6a9-30a1c6497c97 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning A style-based generator architecture for generative adversarial networks

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Observation 0dcf6e1a-a4ab-4a7d-8b86-fd36f8fe6f90 · outbound

This paper cites Training generative adversarial networks with limited data.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Training generative adversarial networks with limited data

Reference 80

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Observation 83060158-189b-44e6-b222-bf5995978336 · outbound

This paper cites Analyzing and improving the image quality of stylegan.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Analyzing and improving the image quality of stylegan

Reference 81

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Observation c0f67931-2fb2-4881-af8a-da6643180201 · outbound

This paper cites Alias-free generative adversarial networks.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Alias-free generative adversarial networks

Reference 82

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Observation 122be77e-4532-4630-82b1-02c353f624ef · outbound

This paper cites Design amortization for bayesian optimal experimental design.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Design amortization for bayesian optimal experimental design

Reference 83

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Observation 3fac4448-86bd-478d-882a-93e00163f06c · outbound

This paper cites Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation

Reference 84

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Observation b401ba84-2259-47dc-b396-97465d0cca7e · outbound

This paper cites Kingma and Jimmy Ba.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Kingma and Jimmy Ba

Reference 85

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Observation b6081e1d-b067-4a68-9003-329d2709e154 · outbound

This paper cites Glow: Generative Flow with Invertible 1x1 Convolutions.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Glow: Generative Flow with Invertible 1x1 Convolutions

Reference 86

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Observation 92d882ff-aa7b-408e-8c1f-0cb7d317e749 · outbound

This paper cites Kingma and Ruiqi Gao.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Kingma and Ruiqi Gao

Reference 87

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Observation a864a28b-96db-4f86-a974-3e4c2c39a478 · outbound

This paper cites Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling

Reference 88

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Observation 3f450f9e-2b3b-426e-bd59-0ace67173e3b · outbound

This paper cites Big transfer (bit): General visual representation learning, 2020.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Big transfer (bit): General visual representation learning, 2020

Reference 89

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Observation aa150093-0620-4e85-b3ca-94a6fb1cb592 · outbound

This paper cites Revealing the dark secrets of BERT.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Revealing the dark secrets of BERT

Reference 90

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Observation 8ba03784-9fe4-42c3-9fd4-41d6be1157c3 · outbound

This paper cites Learning multiple layers of features from tiny images.(2009), 2009.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Learning multiple layers of features from tiny images.(2009), 2009

Reference 91

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Observation 34e16a40-0add-4478-9959-b87d89b64cde · outbound

This paper cites The role of imagenet classes in fr´ echet inception distance.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning The role of imagenet classes in fr´ echet inception distance

Reference 92

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Observation 6f23a532-41c4-4324-bd4d-6d2df39ca268 · outbound

This paper cites Howard, Wayne Hubbard, and Lawrence Jackel.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Howard, Wayne Hubbard, and Lawrence Jackel

Reference 93

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Observation 6ca5c8df-7dd9-4c9d-b261-e5c3942fb104 · outbound

This paper cites Gradient-based learning applied to document recognition.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Gradient-based learning applied to document recognition

Reference 94

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Observation c8c0bdf2-bb63-4361-9926-1fa0f2ac10a5 · outbound

This paper cites Smooth manifolds.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Smooth manifolds

Reference 95

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Observation 2a069103-5c3a-4e9f-bdf8-bfd39c349184 · outbound

This paper cites ViTGAN: Training GANs with vision transformers.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning ViTGAN: Training GANs with vision transformers

Reference 96

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Observation aaa8493b-b635-4b0f-b43d-caadf969ea35 · outbound

This paper cites SNIP: SINGLE- SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning SNIP: SINGLE- SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY

Reference 97

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Observation 4e625c77-2414-4e96-ab2f-ad8caa186401 · outbound

This paper cites xformers: A modular and hackable transformer modelling library.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning xformers: A modular and hackable transformer modelling library

Reference 98

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Observation c4678edd-262e-4ec6-9a39-723df4516573 · outbound

This paper cites Demographic bias effects on face image synthesis.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Demographic bias effects on face image synthesis

Reference 99

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Observation 08ae80c0-aedf-4df6-a828-0233bd8edae4 · outbound

This paper cites Visualizing the loss landscape of neural nets.

Smaller, Faster, Cheaper: Architectural Designs for Efficient Machine Learning Visualizing the loss landscape of neural nets

Reference 100

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