QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference | Paper Citation Record

Observation d351ed06-ad86-4f2d-9954-40e1bcf195f1 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Imagenet classification with deep convolutional neural networks,

Reference 1

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This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2

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This paper cites Distributed representations of words and phrases and their composi- tionality,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Distributed representations of words and phrases and their composi- tionality,

Reference 3

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Observation 046ae3fa-8364-49a4-8224-61a8211c71cc · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Attention is all you need,

Reference 4

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Observation bef7ba7d-5ae9-4126-9947-f7e857e90871 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference End to End Learning for Self-Driving Cars

Reference 5

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Observation fa98c722-c405-451d-b094-60ef32b11ac9 · outbound

This paper cites Efficient processing of deep neural networks: A tutorial and survey,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Efficient processing of deep neural networks: A tutorial and survey,

Reference 6

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Observation 43340d1a-8306-430f-b9b4-36833528ced3 · outbound

This paper cites Edge intelligence: Paving the last mile of artificial intelligence with edge computing,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Edge intelligence: Paving the last mile of artificial intelligence with edge computing,

Reference 7

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Observation 17a8f6da-6a10-4c97-8433-54ae59a96aa0 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Edge computing: Vision and challenges,

Reference 8

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Observation 4c9cbc6d-7b46-4029-bcbd-32cf14ea9786 · outbound

This paper cites Exploring edge tpu for network intrusion detection in iot,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Exploring edge tpu for network intrusion detection in iot,

Reference 9

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Observation fdfdd3d1-717d-43ac-b0f5-9152863e3552 · outbound

This paper cites A survey on optimized implementation of deep learning models on the nvidia jetson platform,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference A survey on optimized implementation of deep learning models on the nvidia jetson platform,

Reference 10

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Observation f00af3bb-9485-49a2-9bfb-956dc5820ba8 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 11

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Observation 7bd9a537-9464-4531-a645-b99880859ad7 · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 12

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Observation fe2b05fb-4b59-40b0-a433-e3a2fc7330fd · outbound

This paper cites Early stopping-but when?.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Early stopping-but when?

Reference 13

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Observation b8f5c182-edd1-4173-a86f-f2b6df28fa84 · outbound

This paper cites Single-layer vision trans- formers for more accurate early exits with less overhead,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Single-layer vision trans- formers for more accurate early exits with less overhead,

Reference 14

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Observation 24d6a9ed-a5ef-41db-93e0-cbf872b27bb0 · outbound

This paper cites 1xn pattern for pruning convolutional neural networks,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference 1xn pattern for pruning convolutional neural networks,

Reference 15

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Observation d4f8d7aa-1a07-45f7-8964-bc509c304082 · outbound

This paper cites Rethinking the Value of Network Pruning.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Rethinking the Value of Network Pruning

Reference 16

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Observation 00a20c81-f5c6-4dbd-b08b-5eb75fc3d467 · outbound

This paper cites Fast and accurate streaming cnn infer- ence via communication compression on the edge,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Fast and accurate streaming cnn infer- ence via communication compression on the edge,

Reference 17

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Observation efceefb2-06ab-49d2-8fca-7cbf25626e0e · outbound

This paper cites Knowledge Distillation for Mobile Edge Computation Offloading.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Knowledge Distillation for Mobile Edge Computation Offloading

Reference 18

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Observation 46790171-a443-4ebc-b72f-2f36f7ab08c7 · outbound

This paper cites Neurosurgeon: Collaborative intelligence between the cloud and mobile edge,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Neurosurgeon: Collaborative intelligence between the cloud and mobile edge,

Reference 19

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Observation f2f4b6de-ee94-4bc8-97d1-accbbc351181 · outbound

This paper cites Edge assisted real-time object detec- JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 12 tion for mobile augmented reality,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Edge assisted real-time object detec- JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 12 tion for mobile augmented reality,

Reference 20

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Observation 0eb223a7-1a00-4644-8c14-e56cf2414fde · outbound

This paper cites Machine learning at face- book: Understanding inference at the edge,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Machine learning at face- book: Understanding inference at the edge,

Reference 21

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Observation 541dfd9a-7240-4ae4-b175-7bbf14c2d0b3 · outbound

This paper cites From smart to deep: Robust activ- ity recognition on smartwatches using deep learning,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference From smart to deep: Robust activ- ity recognition on smartwatches using deep learning,

Reference 22

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Observation dcdbb5d8-54da-44b7-84bc-b03a8bf1fb82 · outbound

This paper cites On- device learning systems for edge intelligence: A software and hardware synergy perspective,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference On- device learning systems for edge intelligence: A software and hardware synergy perspective,

Reference 23

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Observation c5e1af97-efc4-4961-8c66-0f1ddba2d797 · outbound

This paper cites Federated learning over wireless fading channels,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Federated learning over wireless fading channels,

Reference 24

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Observation b126a1ef-b594-4b6a-b68e-3bee7279ee2c · outbound

This paper cites A mathematical theory of communication,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference A mathematical theory of communication,

Reference 25

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Observation 2e248a8c-3bf2-470b-a78b-72ea595fe839 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Deep learning for healthcare: review, opportunities and challenges,

Reference 26

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Observation ac9c8a65-4857-42e6-aab2-d41a28535b99 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Application of deep learning on iot-enabled smart grid monitoring,

Reference 27

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Observation 8d0092bc-e24d-476b-843d-51bc03050ae9 · outbound

This paper cites Recommended for you: The netflix prize and the production of algorithmic culture,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Recommended for you: The netflix prize and the production of algorithmic culture,

Reference 28

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Observation b0c19d02-857b-45a7-b367-18a977f9bdbe · outbound

This paper cites Sentiment analysis with machine learning methods on social media,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Sentiment analysis with machine learning methods on social media,

Reference 29

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Observation ff72a904-1c67-4ca9-9f68-43ad355853ba · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 30

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Observation 57ff7678-8f97-4b5b-bd76-1b82b32f9ca1 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Energy-efficient neural networks using approximate computation reuse,

Reference 31

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Observation 85a2a24c-1fa1-4d58-b19b-7f91c1424450 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Edge ai: On-demand accelerating deep neural network inference via edge computing,

Reference 32

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Observation 6a892d18-6632-42ae-a36c-be28755c8ffc · outbound

This paper cites Adaptive quantization for deep neural network,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Adaptive quantization for deep neural network,

Reference 33

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Observation 509eac9d-a92d-4cc4-8c11-01b4e8a7ddbf · outbound

This paper cites Energy-aware inference offloading for dnn-driven applications in mobile edge clouds,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Energy-aware inference offloading for dnn-driven applications in mobile edge clouds,

Reference 34

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Observation 3ba7a7c2-e4b7-4516-af70-edc2d22bbf44 · outbound

This paper cites Deep compressive offloading: Speeding up neural network inference by trading edge computation for network latency,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Deep compressive offloading: Speeding up neural network inference by trading edge computation for network latency,

Reference 35

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Observation 2e76dccd-abf5-4351-9051-2decd94387e9 · outbound

This paper cites Dis- tributed inference acceleration with adaptive dnn partitioning and of- floading,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Dis- tributed inference acceleration with adaptive dnn partitioning and of- floading,

Reference 36

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Observation cc004271-fbe7-4064-bdcd-a430a27099a6 · outbound

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Computation offloading for fast cnn inference in edge computing,

Reference 37

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Observation ec961cc9-bebb-4d3d-b397-d5e838463c3e · outbound

This paper cites Optimiza- tion of offloading policies for accuracy-delay tradeoffs in hierarchical inference,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Optimiza- tion of offloading policies for accuracy-delay tradeoffs in hierarchical inference,

Reference 38

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Observation 9de7014b-d5e1-4c87-a094-276bba4cf9fd · outbound

This paper cites Multi-agent deep reinforcement learning-based inference task schedul- ing and offloading for maximum inference accuracy under time and energy constraints,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Multi-agent deep reinforcement learning-based inference task schedul- ing and offloading for maximum inference accuracy under time and energy constraints,

Reference 39

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Observation 9d58aa05-0ea3-49c5-97a4-176edc518de6 · outbound

This paper cites {INFaaS}: Automated model-less inference serving,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference {INFaaS}: Automated model-less inference serving,

Reference 40

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Observation acbfd875-c711-4b6e-9d4b-186535ed52f8 · outbound

This paper cites Fann-on-mcu: An open-source toolkit for energy-efficient neural network inference at the edge of the internet of things,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Fann-on-mcu: An open-source toolkit for energy-efficient neural network inference at the edge of the internet of things,

Reference 41

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Observation ee8af57e-d9d2-4e2d-baa9-366f5a3294e9 · outbound

This paper cites Construct- ing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Construct- ing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence,

Reference 42

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Observation 1bf61d5f-d719-4fca-8d47-9765fe6e78c6 · outbound

This paper cites Decision early-exit: An efficient approach to hasten offloading in branchynets,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Decision early-exit: An efficient approach to hasten offloading in branchynets,

Reference 43

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Observation 89d76a53-4fdb-4ca4-b5cf-c678adecbbb5 · outbound

This paper cites A deep reinforcement learning based research for optimal offloading decision,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference A deep reinforcement learning based research for optimal offloading decision,

Reference 44

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Observation a64a0083-8c77-4bd7-807a-ca78be6fda7d · outbound

This paper cites Improving device-edge cooperative inference of deep learning via 2-step pruning,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Improving device-edge cooperative inference of deep learning via 2-step pruning,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.226137Z

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Observation 361532fe-98d9-4a90-adcd-951a51ce857f · outbound

This paper cites Graph reinforcement learning-based cnn inference offloading in dynamic edge computing,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Graph reinforcement learning-based cnn inference offloading in dynamic edge computing,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.208176Z

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Observation 79384222-4789-44c1-b7f0-b994714cd591 · outbound

This paper cites Adaee: Adaptive early-exit dnn inference through multi-armed bandits,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Adaee: Adaptive early-exit dnn inference through multi-armed bandits,

Reference 47

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Observation fccb6195-fadf-4428-8ab1-e60967e7d86d · outbound

This paper cites Optimizing job offloading schedule for collabora- tive dnn inference,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Optimizing job offloading schedule for collabora- tive dnn inference,

Reference 48

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Observation dd605dc4-366f-497e-8863-08e8d0494527 · outbound

This paper cites Improving the accuracy-latency trade-off of edge-cloud com- putation offloading for deep learning services,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Improving the accuracy-latency trade-off of edge-cloud com- putation offloading for deep learning services,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.157257Z

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Observation d20b042d-fae4-45ab-9320-76ebc8e5c031 · outbound

This paper cites Selective Task offloading for Maximum Inference Accuracy and Energy efficient Real-Time IoT Sensing Systems.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Selective Task offloading for Maximum Inference Accuracy and Energy efficient Real-Time IoT Sensing Systems

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:39:19.910331Z

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This paper cites Energy consump- tion of neural networks on nvidia edge boards: an empirical model,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Energy consump- tion of neural networks on nvidia edge boards: an empirical model,

Reference 51

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This paper cites The en- ergy/frequency convexity rule: Modeling and experimental validation on mobile devices,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference The en- ergy/frequency convexity rule: Modeling and experimental validation on mobile devices,

Reference 52

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This paper cites Processor design for portable systems,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Processor design for portable systems,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.103522Z

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This paper cites Going deeper with embedded fpga platform for convolutional neural network,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Going deeper with embedded fpga platform for convolutional neural network,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.086632Z

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This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 55

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Observation f2c5f1d5-ed07-42f3-b7ba-ce7d964d1a4c · outbound

This paper cites Quantized neural networks: Training neural networks with low pre- cision weights and activations,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Quantized neural networks: Training neural networks with low pre- cision weights and activations,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.068479Z

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Observation 730343f9-6174-44f4-aab3-63d12d7caa26 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 57

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Observation 070e2c20-c447-4745-9363-20e1a8913c5d · outbound

This paper cites Deep reinforcement learning-based anti-jamming algorithm using dual action network,.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Deep reinforcement learning-based anti-jamming algorithm using dual action network,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:20.051592Z

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Observation 8fef64d1-49ce-48ed-b343-71fc7081fe76 · outbound

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

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference Gradient-based learning applied to document recognition,

Reference 59

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