EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI | Paper Citation Record

Observation 8a046f65-d4dd-4024-969b-49a521ba9cb2 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Imagenet: A large-scale hierarchical image database

Reference 1

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Observation 29d2a971-e160-42b2-9759-dfb75adcdb14 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Microsoft coco: Common objects in context,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.345212Z

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Observation 1183d727-9043-4f55-a48a-5b04eac7d2bd · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Efficientnet: Rethinking model scaling for convo- lutional neural networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.407100Z

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Observation 692f006f-d91d-4516-8434-f74e4f53e86b · outbound

This paper cites Designing network design spaces,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Designing network design spaces,

Reference 4

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Observation 47ee679b-bc04-44c9-be48-04c3ee2c23e1 · outbound

This paper cites A convnet for the 2020s,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI A convnet for the 2020s,

Reference 5

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Observation ce83e113-4041-42a9-b879-f512b0aa2770 · outbound

This paper cites Edge computing: Vision and challenges,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Edge computing: Vision and challenges,

Reference 6

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Observation f2173493-1a87-481b-bd67-35f320f411ce · outbound

This paper cites Update compression for deep neural networks on the edge,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Update compression for deep neural networks on the edge,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.402221Z

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Observation 9abb729c-4370-4d5a-8432-2fd8af121b62 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Mobilenetv2: Inverted residuals and linear bottle- necks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.377498Z

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Observation 3b4243f8-4917-4d41-a0ea-fed1d1db4bb4 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Mnasnet: Platform-aware neural architecture search for mobile,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.374182Z

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Observation 0d52e1bd-fea8-4cb8-ba5c-9ac11ebdeb1b · outbound

This paper cites Dynamic resolution network,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Dynamic resolution network,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.331064Z

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Observation 1233fa3f-15e5-42c6-bfac-ff46311d15cb · outbound

This paper cites Hrank: Filter pruning using high-rank feature map,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Hrank: Filter pruning using high-rank feature map,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.412228Z

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Observation 4c5d7915-a8f8-47c7-ba39-c58137f14d16 · outbound

This paper cites Convolutional neural network pruning with structural redundancy reduction,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Convolutional neural network pruning with structural redundancy reduction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.369289Z

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Observation 56168db5-e2de-4f33-a435-9d7f128d77d5 · outbound

This paper cites Slimmable neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Slimmable neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.358515Z

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Observation 71abaab2-8159-427b-be1d-b45a5754ee4d · outbound

This paper cites Importance estimation for neural network pruning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Importance estimation for neural network pruning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.372597Z

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Observation 4b0b0839-d8e7-42bb-8d5c-62a62663ea65 · outbound

This paper cites DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:26:36.954380Z

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Observation 798f0d20-511c-44ad-a914-d9a430f6b84c · outbound

This paper cites Decore: Deep compression with reinforcement learning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Decore: Deep compression with reinforcement learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.382361Z

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Observation 318c22ea-5ba7-4c52-b463-04587e75b8e1 · outbound

This paper cites Glance and focus: A dynamic approach to reducing spatial redundancy in image classification,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Glance and focus: A dynamic approach to reducing spatial redundancy in image classification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.385716Z

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Observation ef71f83a-ab42-424a-ab76-592b81d53abe · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 18

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Observation 35aa6036-07e6-47bd-96c0-81a3d7ddb9f4 · outbound

This paper cites Ssd: Single shot multibox detector,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Ssd: Single shot multibox detector,

Reference 19

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Observation dfe6d824-74c3-43d1-a966-8bde2cb3baa4 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.332677Z

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Observation af843880-c3f7-418e-8d2d-e2bb21afbea5 · outbound

This paper cites Mask r-cnn,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Mask r-cnn,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.417303Z

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Observation f5d8b722-87fe-4bfb-98fe-ba238a437869 · outbound

This paper cites The pascal visual object classes (voc) challenge,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI The pascal visual object classes (voc) challenge,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.387387Z

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Observation 0c04ca1b-fd2e-442b-b762-a71112ba65d7 · outbound

This paper cites Unsupervised object discovery and co-localization by deep descriptor transformation,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Unsupervised object discovery and co-localization by deep descriptor transformation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.343624Z

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Observation e0455b16-4b54-4635-a04e-65342614b804 · outbound

This paper cites Rethinking the route towards weakly supervised object localization,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Rethinking the route towards weakly supervised object localization,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.375841Z

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Observation 19e691af-08cd-4975-b2ba-29b16935f9ed · outbound

This paper cites Learning deep features for discriminative localization,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Learning deep features for discriminative localization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.422277Z

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Observation 319f8e9b-6353-42af-81f6-726703fa64f8 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.395619Z

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Observation dae90626-c7b6-4e35-9f92-af58fe67c203 · outbound

This paper cites Adversarial complementary learning for weakly supervised object localization,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Adversarial complementary learning for weakly supervised object localization,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.367620Z

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Observation 310c3b26-f629-4d75-93d0-14838a02f07e · outbound

This paper cites Bringing ai to edge: From deep learning’s perspective,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Bringing ai to edge: From deep learning’s perspective,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.413895Z

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Observation a2c19f64-cb0d-4a60-857b-3cbbefda73d5 · outbound

This paper cites Layer pruning for obtaining shallower resnets,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Layer pruning for obtaining shallower resnets,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.348620Z

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Observation 30b7b61f-3258-4632-97f8-311239f42ea6 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Branchynet: Fast inference via early exiting from deep neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.390566Z

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Observation 1f0eb744-6d6d-46c0-ac7b-8a562f331be4 · outbound

This paper cites Multi-scale dense networks for resource efficient image classification,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Multi-scale dense networks for resource efficient image classification,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.347019Z

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Observation 1f2658c8-f774-4e34-8518-8b7ef896aaf6 · outbound

This paper cites Adaptive neural networks for efficient inference,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Adaptive neural networks for efficient inference,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.365987Z

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Observation b9595270-271d-4af2-8430-c3ac92e44cca · outbound

This paper cites Adaptive Computation Time for Recurrent Neural Networks.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Adaptive Computation Time for Recurrent Neural Networks

Reference 33

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Observation 188c0187-e5b0-4a48-9a64-6415f9c4ff3b · outbound

This paper cites Skipnet: Learning dynamic routing in convolutional networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Skipnet: Learning dynamic routing in convolutional networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.342040Z

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Observation 1247d3a0-6732-49fc-b36d-17a5d6795f7a · outbound

This paper cites Convolutional networks with adaptive infer- ence graphs,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Convolutional networks with adaptive infer- ence graphs,

Reference 35

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Observation 7c717072-76eb-44f3-a6c0-2e8d869aee30 · outbound

This paper cites Channel gating neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Channel gating neural networks,

Reference 36

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Observation 8223500e-7c47-4112-b225-d5437640cee0 · outbound

This paper cites Runtime neural pruning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Runtime neural pruning,

Reference 37

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Observation 7502524c-33a3-4a91-b677-5c19e4416849 · outbound

This paper cites Dynamic channel pruning: Feature boosting and sup- pression,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Dynamic channel pruning: Feature boosting and sup- pression,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.397254Z

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Observation c8c2439d-200e-4b02-a908-eb7648c19426 · outbound

This paper cites Channel selection using gumbel softmax,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Channel selection using gumbel softmax,

Reference 39

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Observation e51cf6ce-9a47-42b1-bbe2-4bb52d800751 · outbound

This paper cites Resolution adaptive networks for efficient inference,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Resolution adaptive networks for efficient inference,

Reference 40

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Observation 4c079a55-1887-490d-b78c-9caf522cf651 · outbound

This paper cites Deep residual learning for image recognition,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Deep residual learning for image recognition,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.353675Z

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Observation 78f813fd-aaa8-4bcb-a360-c8edf594e20f · outbound

This paper cites Tiny-dsod: Lightweight object detection for resource- restricted usages,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Tiny-dsod: Lightweight object detection for resource- restricted usages,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.355378Z

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Observation 0ba90781-a8de-43ec-ae18-e35477d3fe78 · outbound

This paper cites Adam: A method for stochastic optimization.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Adam: A method for stochastic optimization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.350157Z

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Observation 32f9b8e6-4a72-4914-9928-1b3b2b8ddc71 · outbound

This paper cites An exponential learning rate schedule for deep learning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI An exponential learning rate schedule for deep learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.393980Z

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Observation b76a3f3c-56d5-4544-a8e4-75ba963501c9 · outbound

This paper cites Hapi: Hardware-aware progressive inference,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Hapi: Hardware-aware progressive inference,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.356982Z

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Observation 6f685cff-09e0-4739-9b04-fe14622ee67c · outbound

This paper cites Shallow-deep networks: Understanding and mitigating network overthinking,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Shallow-deep networks: Understanding and mitigating network overthinking,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.364192Z

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Observation 4db65c55-610a-4716-ad46-3e9ab0e6d179 · outbound

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

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:26:36.956582Z

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Observation 325d1e26-664b-4eb9-a53c-53acc245c5ca · outbound

This paper cites Rethinking the inception architecture for computer vision,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Rethinking the inception architecture for computer vision,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.384019Z

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Observation b2c225a4-6d46-477f-8111-c5bf6ca3fd35 · outbound

This paper cites Wide residual networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Wide residual networks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.338715Z

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Observation 1fb16f3a-3435-472b-bfc5-56c996fad770 · outbound

This paper cites Data-driven sparse structure selection for deep neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Data-driven sparse structure selection for deep neural networks,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.410563Z

Source-reported events for the cited work

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Observation e5938fca-b86e-4f1a-9a1c-150671381171 · outbound

This paper cites Learning versatile filters for efficient convolutional neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Learning versatile filters for efficient convolutional neural networks,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.403937Z

Source-reported events for the cited work

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Observation f319b51e-bdff-4081-9907-c11a41baeff7 · outbound

This paper cites Provable filter pruning for efficient neural networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Provable filter pruning for efficient neural networks,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.415720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a6e6bdb7-f4dd-4f07-a819-d5d36223bddf · outbound

This paper cites Centripetal sgd for pruning very deep convolutional networks with complicated structure,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Centripetal sgd for pruning very deep convolutional networks with complicated structure,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.340406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a0ae7f46-2b48-4a42-a994-9bce28e9aaa9 · outbound

This paper cites Towards optimal structured cnn pruning via generative adversarial learning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Towards optimal structured cnn pruning via generative adversarial learning,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.408883Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f48327a2-9f46-4b07-badf-43983714f94c · outbound

This paper cites Autopruner: An end-to-end trainable filter pruning method for efficient deep model inference,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Autopruner: An end-to-end trainable filter pruning method for efficient deep model inference,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.334362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0ec14429-5fef-4c89-ac3e-5e75e5f5c3a7 · outbound

This paper cites Densely connected convolutional networks,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Densely connected convolutional networks,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.360855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bece9939-3897-4794-9b62-0ae34bfac5b7 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Batch normalization: Accelerating deep network training by reducing internal covariate shift,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.370960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bae9f694-88d1-4512-861e-010fa9b61297 · outbound

This paper cites Variational convolutional neural network pruning,.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI Variational convolutional neural network pruning,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.419074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46bfbdbd-ba8c-400e-a76b-e884ea79264d · outbound

This paper cites His current research interests include edge intelli- gence, hardware-aware neural architecture search, and model compression.

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI His current research interests include edge intelli- gence, hardware-aware neural architecture search, and model compression

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T22:26:37.379251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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