MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks | Paper Citation Record

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This paper cites Intelligent health care: Applications of deep learning in computational medicine,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Intelligent health care: Applications of deep learning in computational medicine,

Reference 1

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This paper cites A survey on deep learning for cybersecurity: Progress, challenges, and opportunities,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A survey on deep learning for cybersecurity: Progress, challenges, and opportunities,

Reference 2

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This paper cites A survey of deep learning techniques for autonomous driving,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A survey of deep learning techniques for autonomous driving,

Reference 3

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This paper cites Edge artificial intelligence for internet of things devices: Open challenges,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Edge artificial intelligence for internet of things devices: Open challenges,

Reference 4

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This paper cites Prunet: Class- blind pruning method for deep neural networks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Prunet: Class- blind pruning method for deep neural networks,

Reference 5

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This paper cites Methods for pruning deep neural networks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Methods for pruning deep neural networks,

Reference 6

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This paper cites A cross-layer approach towards de- veloping efficient embedded deep learning systems,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A cross-layer approach towards de- veloping efficient embedded deep learning systems,

Reference 7

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Observation e9da866b-18a5-42dc-853b-5bc890f20a76 · outbound

This paper cites Quantization of deep neural networks for accurate edge computing,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Quantization of deep neural networks for accurate edge computing,

Reference 8

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Observation 6c7f329d-5e83-449a-b7ff-9df36f24599b · outbound

This paper cites Head network distillation: Splitting distilled deep neural networks for resource-constrained edge computing systems,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Head network distillation: Splitting distilled deep neural networks for resource-constrained edge computing systems,

Reference 9

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Observation 602c6c46-752e-41fe-9990-263e12560f33 · outbound

This paper cites A Comprehensive Survey on Hardware-Aware Neural Architecture Search.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A Comprehensive Survey on Hardware-Aware Neural Architecture Search

Reference 10

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This paper cites Fast hardware-aware neural architecture search,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fast hardware-aware neural architecture search,

Reference 11

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Observation 8da88fb8-9281-445b-8f39-4fc22590f02d · outbound

This paper cites Automl: A survey of the state-of-the-art,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Automl: A survey of the state-of-the-art,

Reference 12

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Observation e5cd76e1-be9e-498b-8107-a392a36ac724 · outbound

This paper cites Neural architecture search: A survey,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Neural architecture search: A survey,

Reference 13

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This paper cites A Survey on Neural Architecture Search.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A Survey on Neural Architecture Search

Reference 14

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This paper cites Nascaps: A framework for neural architecture search to optimize the accuracy and hardware efficiency of convolutional capsule networks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Nascaps: A framework for neural architecture search to optimize the accuracy and hardware efficiency of convolutional capsule networks,

Reference 15

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This paper cites Bionetexplorer: Architecture-space exploration of biosignal processing deep neural networks for wearables,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Bionetexplorer: Architecture-space exploration of biosignal processing deep neural networks for wearables,

Reference 16

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This paper cites Kaisa, Nonlinear Multiobjective Optimization.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Kaisa, Nonlinear Multiobjective Optimization

Reference 17

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Observation 3c26d219-5eaf-4bc7-a1e9-0ba824e7763a · outbound

This paper cites The larger the fairer? small neural networks can achieve fairness for edge devices,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks The larger the fairer? small neural networks can achieve fairness for edge devices,

Reference 18

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Observation b485b7bc-842c-4efb-8981-29abf5baed1f · outbound

This paper cites A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?

Reference 19

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This paper cites Robust re-identification by multiple views knowledge distillation,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Robust re-identification by multiple views knowledge distillation,

Reference 20

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This paper cites Domain generalization: A survey,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Domain generalization: A survey,

Reference 21

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Observation 30b33df6-6f05-49d7-a039-5cfde969ae8a · outbound

This paper cites Deep learning-enabled medical computer vision,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Deep learning-enabled medical computer vision,

Reference 22

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This paper cites A survey on bias and fairness in machine learning,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A survey on bias and fairness in machine learning,

Reference 23

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This paper cites Do imagenet classifiers generalize to imagenet?,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Do imagenet classifiers generalize to imagenet?,

Reference 24

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This paper cites The Robustness Limits of SoTA Vision Models to Natural Variation.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks The Robustness Limits of SoTA Vision Models to Natural Variation

Reference 25

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This paper cites Fair ai: Challenges and opportunities,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fair ai: Challenges and opportunities,

Reference 26

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This paper cites Fairness by explica- bility and adversarial shap learning,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fairness by explica- bility and adversarial shap learning,

Reference 27

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This paper cites Social-minded measures of data quality: fairness, diversity, and lack of bias,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Social-minded measures of data quality: fairness, diversity, and lack of bias,

Reference 28

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This paper cites Fairness for deep learning predic- tions using bias parity score based loss function regularization,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fairness for deep learning predic- tions using bias parity score based loss function regularization,

Reference 29

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This paper cites Microsoft coco: Common objects in context,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Microsoft coco: Common objects in context,

Reference 30

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This paper cites Facet: Fairness in computer vision evaluation benchmark,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Facet: Fairness in computer vision evaluation benchmark,

Reference 31

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This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 32

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This paper cites Fairness perceptions of artificial intelligence: A review and path forward,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fairness perceptions of artificial intelligence: A review and path forward,

Reference 33

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This paper cites Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision chal- lenge,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision chal- lenge,

Reference 34

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This paper cites Understanding deep learning (still) requires rethinking generalization,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Understanding deep learning (still) requires rethinking generalization,

Reference 35

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This paper cites Fair data generation and ma- chine learning through generative adversarial networks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fair data generation and ma- chine learning through generative adversarial networks,

Reference 36

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This paper cites Data preprocessing to mitigate bias: A maximum entropy based approach,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Data preprocessing to mitigate bias: A maximum entropy based approach,

Reference 37

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This paper cites Ditto: Fair and robust federated learning through personalization,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Ditto: Fair and robust federated learning through personalization,

Reference 38

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Observation 605ba2b6-d67a-4a9f-b68f-cd0c3f9b7c49 · outbound

This paper cites Fairness in deep learning: A survey on vision and language research,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Fairness in deep learning: A survey on vision and language research,

Reference 39

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This paper cites A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas,

Reference 40

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This paper cites Mobilenetv3,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Mobilenetv3,

Reference 41

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

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 42

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This paper cites Ensemble learning techniques and its efficiency in machine learning: A survey,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Ensemble learning techniques and its efficiency in machine learning: A survey,

Reference 43

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This paper cites Glam: Efficient scaling of language models with mixture- of-experts,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Glam: Efficient scaling of language models with mixture- of-experts,

Reference 44

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This paper cites Scaling vision with sparse mixture of experts,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Scaling vision with sparse mixture of experts,

Reference 45

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This paper cites Synergy-of-experts: Collaborate to improve adversarial robustness,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Synergy-of-experts: Collaborate to improve adversarial robustness,

Reference 46

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This paper cites Balanced product of calibrated experts for long-tailed recognition,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Balanced product of calibrated experts for long-tailed recognition,

Reference 47

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This paper cites Attention is all you need,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Attention is all you need,

Reference 48

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This paper cites Transformers in vision: A survey,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Transformers in vision: A survey,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.357100Z

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This paper cites Bananas: Bayesian optimiza- tion with neural architectures for neural architecture search,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Bananas: Bayesian optimiza- tion with neural architectures for neural architecture search,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.342646Z

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This paper cites Scalability of the bayesian optimization algorithm,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Scalability of the bayesian optimization algorithm,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.329504Z

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This paper cites Task-Specific Expert Pruning for Sparse Mixture-of-Experts.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Task-Specific Expert Pruning for Sparse Mixture-of-Experts

Reference 52

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MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Timm top 20 fastest models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.316365Z

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Observation d5874a03-b3b7-4798-9062-76710969e7f8 · outbound

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

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.303527Z

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Observation 1960c5b3-63a0-4c3b-9f50-c370786c6b31 · outbound

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MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks RepGhost: A Hardware-Efficient Ghost Module via Re-parameterization

Reference 55

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MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks PP-LCNet: A Lightweight CPU Convolutional Neural Network

Reference 56

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MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Separable Self-attention for Mobile Vision Transformers

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T12:54:26.985619Z

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This paper cites Mobilenetv2: Inverted residuals and linear bottle- necks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Mobilenetv2: Inverted residuals and linear bottle- necks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.290575Z

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This paper cites Deep residual learning for image recognition,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Deep residual learning for image recognition,

Reference 59

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Observation 8be868f4-5041-44c8-88d0-ddbeba8ece1c · outbound

This paper cites Mnasnet: Platform-aware neural architecture search for mobile,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Mnasnet: Platform-aware neural architecture search for mobile,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.267830Z

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

Observation c31964df-8f9e-4bd2-8e09-4c5ef7408dbf · outbound

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MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Searching for mobilenetv3,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.254686Z

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Observation e1db6175-54c5-467b-881f-6b2d0fb7db88 · outbound

This paper cites Model rubik’s cube: Twisting resolution, depth and width for tinynets,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Model rubik’s cube: Twisting resolution, depth and width for tinynets,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.240979Z

Source-reported events for the cited work

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Observation 8a05049b-5653-4edf-a2da-fcbe0bfa8ce0 · outbound

This paper cites ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Reference 63

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

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Imagenet: A large-scale hierarchical image database,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.227757Z

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

Observation 0b5b4343-ec40-43ea-a39e-2a194b9addf5 · outbound

This paper cites Efficientnet: Rethinking model scaling for convo- lutional neural networks,.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Efficientnet: Rethinking model scaling for convo- lutional neural networks,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:54:27.214112Z

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 43509c4c-9f85-47f2-8b80-10c2e9b3daf5 · outbound

This paper cites Architectural Vision for Quantum Computing in the Edge-Cloud Continuum.

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks Architectural Vision for Quantum Computing in the Edge-Cloud Continuum

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-08T12:54:27.063910Z

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