AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence | Paper Citation Record

Observation 79fa04e9-01c2-4263-b83b-a8f82f830884 · outbound

This paper cites Multi-objective isac for low-altitude economy based on multi-task deep reinforcement learning with mixture of experts,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Multi-objective isac for low-altitude economy based on multi-task deep reinforcement learning with mixture of experts,

Reference 1

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This paper cites Edge computing: Vision and challenges,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Edge computing: Vision and challenges,

Reference 2

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This paper cites A comprehensive survey of mixture-of-experts: Algorithms, theory, and applications,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence A comprehensive survey of mixture-of-experts: Algorithms, theory, and applications,

Reference 3

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

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Scaling vision with sparse mixture of experts,

Reference 4

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This paper cites Wdmoe: Wireless distributed large language models with mixture of experts,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Wdmoe: Wireless distributed large language models with mixture of experts,

Reference 5

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This paper cites Mixture-of-experts for distributed edge computing with channel-aware gating function,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Mixture-of-experts for distributed edge computing with channel-aware gating function,

Reference 6

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This paper cites A unified distributed algorithm for hybrid near-far field activity detection in cell- free massive mimo,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence A unified distributed algorithm for hybrid near-far field activity detection in cell- free massive mimo,

Reference 7

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This paper cites Broadband analog aggregation for low-latency federated edge learning,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Broadband analog aggregation for low-latency federated edge learning,

Reference 8

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This paper cites Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air,

Reference 9

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Observation 41cc7d80-9d54-4533-91ad-8006184958a0 · outbound

This paper cites Over-the-air computing for wire- less data aggregation in massive IoT,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Over-the-air computing for wire- less data aggregation in massive IoT,

Reference 10

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Observation 012c80f5-39e0-41a6-a70b-ff5a949e5f11 · outbound

This paper cites Computation-efficient federated prompt-tuning with vision-language foundation model compression over resource-constrained edge networks,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Computation-efficient federated prompt-tuning with vision-language foundation model compression over resource-constrained edge networks,

Reference 11

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Observation c3420b26-1468-4738-b31e-30ad7e822b67 · outbound

This paper cites Fast ai model partition for split learning over edge networks,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Fast ai model partition for split learning over edge networks,

Reference 12

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Observation d6a47436-8781-4e0d-8bb2-263956b8ed74 · outbound

This paper cites Efficient layer-granularity unloading for llms in edge computing,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Efficient layer-granularity unloading for llms in edge computing,

Reference 13

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Observation 571e76ab-032d-4676-a7a0-3c2838691859 · outbound

This paper cites pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving,

Reference 14

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Observation a1ac8660-341b-4d60-a746-d72dcc1ab15f · outbound

This paper cites BottleNet: A deep learning architecture for intelligent mobile cloud computing services,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence BottleNet: A deep learning architecture for intelligent mobile cloud computing services,

Reference 15

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This paper cites Split computing and early exiting for deep learning applications: Survey and research challenges,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Split computing and early exiting for deep learning applications: Survey and research challenges,

Reference 16

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Observation bcc59dc1-04b7-489b-90bd-c81a0c5f0c88 · outbound

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

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence BranchyNet: Fast inference via early exiting from deep neural networks,

Reference 17

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Observation fec98010-cb4c-4e57-9dfa-6c6526434eb7 · outbound

This paper cites Communication-computation trade-off in resource-constrained edge inference,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Communication-computation trade-off in resource-constrained edge inference,

Reference 18

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Observation c87c8072-1e84-4c6a-97c0-8f7ea2eac2f0 · outbound

This paper cites JointDNN: An efficient training and inference engine for intelligent mobile cloud com- puting services,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence JointDNN: An efficient training and inference engine for intelligent mobile cloud com- puting services,

Reference 19

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Observation 225048d6-3b1f-4300-819f-cff86c782f07 · outbound

This paper cites EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices

Reference 20

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Observation 064fc0e6-7816-4a14-9182-671eb5d33686 · outbound

This paper cites LLM-QAT: Data-free quantization aware training for large language models,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence LLM-QAT: Data-free quantization aware training for large language models,

Reference 21

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Observation ca37dbeb-b552-4643-801e-f294ca2f96d7 · outbound

This paper cites Understanding complex-valued transformer for modulation recognition,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Understanding complex-valued transformer for modulation recognition,

Reference 22

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This paper cites LoRA: Low-rank adaptation of large language models,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence LoRA: Low-rank adaptation of large language models,

Reference 23

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Observation 64d5b3a5-b3e1-4e80-ab89-e1d770ba99b2 · outbound

This paper cites A federated rec- ommendation system framework based on variational autoencoder with mixture of experts,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence A federated rec- ommendation system framework based on variational autoencoder with mixture of experts,

Reference 24

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Observation 9d488fde-56fb-486f-b980-a11b2ede0242 · outbound

This paper cites M 3vit: Mixture-of-experts vision transformer for efficient multi- task learning with model-accelerator co-design,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence M 3vit: Mixture-of-experts vision transformer for efficient multi- task learning with model-accelerator co-design,

Reference 25

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Observation 563d1bc7-0382-4714-a7e4-d0f4f8a74e30 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 26

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Observation 7b6e1595-d3db-46b9-96a4-9051b49a27b8 · outbound

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

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 27

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This paper cites GShard: Scaling giant models with condi- tional computation and automatic sharding,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence GShard: Scaling giant models with condi- tional computation and automatic sharding,

Reference 28

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Observation 111f9527-c02e-43ea-8ceb-e9892e6fd8ed · outbound

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

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence GLaM: Efficient scaling of language models with mixture- of-experts,

Reference 29

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Observation 81547d53-203a-4ffd-a481-92107df200c3 · outbound

This paper cites Mixtral of Experts.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Mixtral of Experts

Reference 30

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This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 31

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This paper cites BASE layers: Simplifying training of large, sparse models,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence BASE layers: Simplifying training of large, sparse models,

Reference 32

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This paper cites Mixture-of-experts with expert choice routing,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Mixture-of-experts with expert choice routing,

Reference 33

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This paper cites Tutel: Adaptive mixture-of-experts at scale,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Tutel: Adaptive mixture-of-experts at scale,

Reference 34

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This paper cites Theory of mixture-of-experts for mobile edge computing,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Theory of mixture-of-experts for mobile edge computing,

Reference 35

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This paper cites Accelerating distributed MoE training and inference with Lina,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Accelerating distributed MoE training and inference with Lina,

Reference 36

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This paper cites Computation over multiple-access channels,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Computation over multiple-access channels,

Reference 37

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This paper cites Fast-convergent and communication-alleviated heterogeneous hierar- chical federated learning in autonomous driving,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Fast-convergent and communication-alleviated heterogeneous hierar- chical federated learning in autonomous driving,

Reference 38

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This paper cites Communication resources constrained hierarchical federated learning for end-to-end autonomous driving,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Communication resources constrained hierarchical federated learning for end-to-end autonomous driving,

Reference 39

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This paper cites Fedrc: A rapid-converged hierarchical federated learning framework in street scene semantic understanding,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Fedrc: A rapid-converged hierarchical federated learning framework in street scene semantic understanding,

Reference 40

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This paper cites Fedema: Federated exponential moving averaging with negative entropy regularizer in autonomous driving,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Fedema: Federated exponential moving averaging with negative entropy regularizer in autonomous driving,

Reference 41

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This paper cites Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air,

Reference 42

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This paper cites Federated learning via over- the-air computation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Federated learning via over- the-air computation,

Reference 43

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This paper cites Optimized power control design for over-the-air federated edge learning,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Optimized power control design for over-the-air federated edge learning,

Reference 44

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This paper cites StableMoE: Stable routing strategy for mixture of experts,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence StableMoE: Stable routing strategy for mixture of experts,

Reference 46

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This paper cites Hash layers for large sparse models,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Hash layers for large sparse models,

Reference 47

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This paper cites The cityscapes dataset for semantic urban scene understanding,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence The cityscapes dataset for semantic urban scene understanding,

Reference 48

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This paper cites Segmentation and recognition using structure from motion point clouds,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Segmentation and recognition using structure from motion point clouds,

Reference 49

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This paper cites The apolloscape open dataset for autonomous driving and its application,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence The apolloscape open dataset for autonomous driving and its application,

Reference 50

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This paper cites Carla: An open urban driving simulator,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Carla: An open urban driving simulator,

Reference 51

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Observation 8164e373-c86f-4a06-809a-dd69ffee7f10 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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Observation 58cc84fe-63f5-4532-a925-81698dc18c33 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Rethinking Atrous Convolution for Semantic Image Segmentation

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This paper cites Statistical Advantages of Perturbing Cosine Router in Mixture of Experts.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Statistical Advantages of Perturbing Cosine Router in Mixture of Experts

Reference 54

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This paper cites From sparse to soft mixtures of experts,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence From sparse to soft mixtures of experts,

Reference 55

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This paper cites Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation,

Reference 56

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This paper cites Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,

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Observation 9ad9caa7-36b3-4329-bf14-b47e480dea29 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Segformer: Simple and efficient design for semantic segmentation with transformers,

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Observation dd939b25-6282-4bcb-9c1c-48e31c7eb20a · outbound

This paper cites Attanet: Attention-augmented network for fast and accurate scene parsing,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Attanet: Attention-augmented network for fast and accurate scene parsing,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T20:38:32.680945Z

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Observation 1d23fa5e-4452-40de-9e38-cba7b9e4abd5 · outbound

This paper cites Domain adaptive and general- izable network architectures and training strategies for semantic image segmentation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Domain adaptive and general- izable network architectures and training strategies for semantic image segmentation,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-01T20:38:32.820412Z

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Observation 26b3c558-43f2-4444-a72c-354fba9f4d86 · outbound

This paper cites Topformer: Token pyramid transformer for mobile semantic segmentation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Topformer: Token pyramid transformer for mobile semantic segmentation,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T20:38:32.957905Z

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Observation ca6a7559-f66a-4d65-87d9-b1ccb3cc8201 · outbound

This paper cites Seaformer: Squeeze- enhanced axial transformer for mobile semantic segmentation,.

AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence Seaformer: Squeeze- enhanced axial transformer for mobile semantic segmentation,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T20:38:33.102553Z

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