FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning | Paper Citation Record

Observation 74f60fd0-3b23-4e1d-9bbf-2a6f07c9d2c6 · outbound

This paper cites Adaptive federated learning and digital twin for industrial internet of things.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Adaptive federated learning and digital twin for industrial internet of things

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Observation 5df4e07c-7692-4f3c-9d0f-ebf3781a0436 · outbound

This paper cites Digital twin driven smart factories: real time physics based co-simulation using edge ai and federated learning.Scientific Reports, 15(1):43373, 2025.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Digital twin driven smart factories: real time physics based co-simulation using edge ai and federated learning.Scientific Reports, 15(1):43373, 2025

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.621498Z

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Observation 452505bf-8f3a-4645-8e19-b56f6ddb2416 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Communication-efficient learning of deep networks from decentralized data

Reference 3

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This paper cites Edge-basedcommunicationoptimizationfordistributedfederated learning.IEEE Transactions on Network Science and Engineering, 9 (4):2015–2024, 2021.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Edge-basedcommunicationoptimizationfordistributedfederated learning.IEEE Transactions on Network Science and Engineering, 9 (4):2015–2024, 2021

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.597175Z

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Observation 856c2522-5aaa-455f-af2d-652dc50a38e6 · outbound

This paper cites an unresolved cited work.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Unresolved cited work

Reference 5

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Observation 70d86eb6-b9d8-40d7-a3bf-e0d4f5de5d92 · outbound

This paper cites Yu, and Christo- pher G.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Yu, and Christo- pher G

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.581766Z

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Observation dda835c0-8271-4a34-890e-e7a6d98a9d60 · outbound

This paper cites Fullydecentralizedfederatedlearning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Fullydecentralizedfederatedlearning

Reference 7

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Observation fe640f00-d937-4799-9d83-9da44bda54d0 · outbound

This paper cites Distributedandsecurefederatedlearningforwirelesscomputingpower networks.IEEE Transactions on Vehicular Technology, 72(7):9381– 9393, 2023.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Distributedandsecurefederatedlearningforwirelesscomputingpower networks.IEEE Transactions on Vehicular Technology, 72(7):9381– 9393, 2023

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.550433Z

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Observation 3d1d22b6-a58e-43e6-bf4f-ecf5d1ee9060 · outbound

This paper cites MC-2PF:Amulti-edgecooperativeuniversalframework for load prediction with personalized federated deep learning.IEEE Transactions on Mobile Computing, 24(6):5138–5154, 2025.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning MC-2PF:Amulti-edgecooperativeuniversalframework for load prediction with personalized federated deep learning.IEEE Transactions on Mobile Computing, 24(6):5138–5154, 2025

Reference 9

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Observation ca7fcc9b-0a9b-4290-b192-1b031faa7d6a · outbound

This paper cites Resilientcollaborativecachingformulti-edgesystemswith robust federated deep learning.IEEE Transactions on Networking, 33 (2):654–669, 2024.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Resilientcollaborativecachingformulti-edgesystemswith robust federated deep learning.IEEE Transactions on Networking, 33 (2):654–669, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.533038Z

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Observation d2950e1e-10c8-4642-8ba4-db97e5f4b51f · outbound

This paper cites Accelerating decentralized federated learning with probabilistic communication in heterogeneous edgecomputing.IEEETransactionsonNetworking,34:486–501,2026.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Accelerating decentralized federated learning with probabilistic communication in heterogeneous edgecomputing.IEEETransactionsonNetworking,34:486–501,2026

Reference 11

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T21:32:13.760909Z

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Observation 5a6473be-c3cd-4535-a392-8dffac0c1b12 · outbound

This paper cites Decentralized edge learning: A comparative study of distillation strategies and dissimilarity measures.Future Generation Computer Systems, 176:108171, 2026.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Decentralized edge learning: A comparative study of distillation strategies and dissimilarity measures.Future Generation Computer Systems, 176:108171, 2026

Reference 12

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Observation 8da4bf41-4c11-42c0-adb1-e5c6aaecb2b4 · outbound

This paper cites Traffic-Aware Lightweight Hierarchical Offloading Toward Adaptive Slicing-EnabledSAGIN.IEEEJournalonSelectedAreasinCommuni- cations, 42(12):3536–3550, 2024.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Traffic-Aware Lightweight Hierarchical Offloading Toward Adaptive Slicing-EnabledSAGIN.IEEEJournalonSelectedAreasinCommuni- cations, 42(12):3536–3550, 2024

Reference 13

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Observation 41c1d4aa-c024-416d-874f-b1a03855e115 · outbound

This paper cites Federated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Federated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.517542Z

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Observation 0d333b1d-fb54-4863-91a4-ebafefdca67a · outbound

This paper cites FedTVD:Balancing data quality and quantity for robust federated learning.Future Generation Computer Systems, page 108177, 2025.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedTVD:Balancing data quality and quantity for robust federated learning.Future Generation Computer Systems, page 108177, 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.501855Z

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Observation 749e5f39-2bcc-4eb3-9929-bcdafdbc78a1 · outbound

This paper cites FedDC: Federated learning with non-IID data via local drift decoupling and correction.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedDC: Federated learning with non-IID data via local drift decoupling and correction

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.486836Z

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Observation 63b9f5c5-0057-4a4c-9350-27cd5b2b585d · outbound

This paper cites Def-Ag: An energy- efficient decentralized federated learning framework via aggregator clients.Future Generation Computer Systems, 175:108114, 2026.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Def-Ag: An energy- efficient decentralized federated learning framework via aggregator clients.Future Generation Computer Systems, 175:108114, 2026

Reference 17

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Observation bd6314b3-aad6-492f-b983-1a00d23bc5f4 · outbound

This paper cites How transferable are features in deep neural networks?Advances in neural information processing systems, 27, 2014.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning How transferable are features in deep neural networks?Advances in neural information processing systems, 27, 2014

Reference 18

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Observation 1f3effc5-8b05-4fa1-8ce4-721b776e5066 · outbound

This paper cites Visualizing and understanding convolutional networks.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Visualizing and understanding convolutional networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.461830Z

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Observation bc74f504-2444-4957-ae96-facd8faa6646 · outbound

This paper cites PLayer-FL: A Principled Approach to Personalized Layer-wise Cross-Silo Federated Learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning PLayer-FL: A Principled Approach to Personalized Layer-wise Cross-Silo Federated Learning

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Resolution: verified exact; local_arxiv, observed 2026-08-11T21:32:13.406629Z

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Observation 316bf59d-c3ae-4e9e-b919-4897956de2a7 · outbound

This paper cites Optimizing personalized federated learning through adaptive layer- wise learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Optimizing personalized federated learning through adaptive layer- wise learning

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Resolution: verified exact; doi, observed 2026-08-11T21:32:14.448036Z

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Observation 07febe22-8cef-4798-b563-e123cf25f248 · outbound

This paper cites Adaptive Federated Optimization.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Adaptive Federated Optimization

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Observation 74531ec5-5527-4bbc-be43-2fa832f28f37 · outbound

This paper cites FLARE: A new federated learning framework with adjustable learning rates over resource-constrained wireless networks.IEEE Transactions on Wireless Communications, 2025.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FLARE: A new federated learning framework with adjustable learning rates over resource-constrained wireless networks.IEEE Transactions on Wireless Communications, 2025

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.433740Z

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Observation 9e0b7d94-dc02-4161-85ce-38493210b529 · outbound

This paper cites Consensus-driven hyperparameter optimization for accelerated model convergence in decentralized federated learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Consensus-driven hyperparameter optimization for accelerated model convergence in decentralized federated learning

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Observation 26647f9f-ae6b-4974-b647-85372e4c5ee1 · outbound

This paper cites AutoLR: Layer-wise pruning and auto-tuning of learning rates in fine-tuning of deep networks.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning AutoLR: Layer-wise pruning and auto-tuning of learning rates in fine-tuning of deep networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.419941Z

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Observation 806d022e-3635-41bb-8f54-8a570b036154 · outbound

This paper cites Fed-LAMB: layer-wise and dimension-wise locally adaptive federated learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Fed-LAMB: layer-wise and dimension-wise locally adaptive federated learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.406445Z

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Observation 53bd831c-078f-4292-b747-1edd24ed2a0b · outbound

This paper cites FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking

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Observation 438aaa65-6205-4a99-94e0-6498d7a4810e · outbound

This paper cites an unresolved cited work.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Unresolved cited work

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Observation 81f1eabb-b701-4b5d-9368-fe4152993cc2 · outbound

This paper cites Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges.IEEE Communications Surveys & Tutorials, 25(4):2983–3013, 2023.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges.IEEE Communications Surveys & Tutorials, 25(4):2983–3013, 2023

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Observation 8b5a8f08-3e77-47a4-80f9-dc202b321bf9 · outbound

This paper cites Enhancing privacy preservation and trustworthiness for decentralized federated learning.Information Sciences, 628:449–468,.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Enhancing privacy preservation and trustworthiness for decentralized federated learning.Information Sciences, 628:449–468,

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Observation 1a10bcff-d28a-47ae-869c-239b128c9c2e · outbound

This paper cites DeFTA:Aplug-and-playpeer-to-peerdecentralizedfederatedlearning framework.InformationSciences,670:120582,2024.ISSN0020-0255.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning DeFTA:Aplug-and-playpeer-to-peerdecentralizedfederatedlearning framework.InformationSciences,670:120582,2024.ISSN0020-0255

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Observation c4192497-4e9c-4da5-8779-7588c09a8a54 · outbound

This paper cites Network topology and communication-computation tradeoffs in decentralized optimization.Proceedings of the IEEE, 106(5):953–976, 2018.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Network topology and communication-computation tradeoffs in decentralized optimization.Proceedings of the IEEE, 106(5):953–976, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.348063Z

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Observation 52791034-a37a-4016-a70f-6bac1ac49e0a · outbound

This paper cites an unresolved cited work.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Unresolved cited work

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Observation 97903101-46e8-414c-be24-61e9188bd9ea · outbound

This paper cites Stich, and Martin Jaggi.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Stich, and Martin Jaggi

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Observation 26cbe862-e0de-461e-b434-1b85496b45c2 · outbound

This paper cites GossipFL:A decentralized federated learning framework with sparsified and adap- tive communication.IEEE Transactions on Parallel and Distributed Systems, 34(3):909–922, 2022.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning GossipFL:A decentralized federated learning framework with sparsified and adap- tive communication.IEEE Transactions on Parallel and Distributed Systems, 34(3):909–922, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.317410Z

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Observation b404066f-fe3e-4291-8789-551413dff707 · outbound

This paper cites FedAWA: Adaptive optimization of aggregation weights in federated learning using client vectors.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedAWA: Adaptive optimization of aggregation weights in federated learning using client vectors

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Observation 238e91e5-8c7b-479d-ae0b-72c07864dfc6 · outbound

This paper cites Adapted weighted aggregation in federated learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Adapted weighted aggregation in federated learning

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Observation 5c5898ff-e97d-480e-9dd4-43bd9c051858 · outbound

This paper cites Federated learning with hyper- parameter optimization.Journal of King Saud University-Computer and Information Sciences, 35(9):101740, 2023.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Federated learning with hyper- parameter optimization.Journal of King Saud University-Computer and Information Sciences, 35(9):101740, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.268462Z

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Observation 1ad1c1ee-5cf2-4876-9f38-c2f65640ad92 · outbound

This paper cites Federated hyperparameter optimization through reward-basedstrategies:Challengesandinsights.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Federated hyperparameter optimization through reward-basedstrategies:Challengesandinsights

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.251509Z

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Observation 85e00e3e-6401-4556-bd9a-82b25f81ac59 · outbound

This paper cites Federated Learning with Non-IID Data.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Federated Learning with Non-IID Data

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This paper cites Federatedlearningvia consensus mechanism on heterogeneous data: A new perspective on convergence.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Federatedlearningvia consensus mechanism on heterogeneous data: A new perspective on convergence

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Observation 3c87edd5-7743-4800-8bee-da02c196ea92 · outbound

This paper cites Learning multiple layers of features from tiny images.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Learning multiple layers of features from tiny images

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.220734Z

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Observation 8fc714e7-3208-401a-8052-e753f171b75d · outbound

This paper cites Tiny imagenet visual recognition challenge.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Tiny imagenet visual recognition challenge

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Resolution: unresolved; no resolver link, observed 2026-08-11T21:32:12.899976Z

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Observation 60aa0b98-58ec-4361-9888-415b18727590 · outbound

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FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-11T21:32:14.193945Z

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Observation 42c50378-5a94-4092-99ab-58d41e8033bb · outbound

This paper cites Cautionary tales on air-quality improvement in beijing.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Cautionary tales on air-quality improvement in beijing

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.178597Z

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Observation 7d84c553-5bc9-4ba6-8222-393ceb162a3d · outbound

This paper cites Timer: generative pre-trained trans- formers are large time series models.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Timer: generative pre-trained trans- formers are large time series models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.161260Z

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Observation 086188f2-0bb3-4569-a260-0e4055d9d1b4 · outbound

This paper cites Preservation of the Global Knowledge by Not-True Distillation in Federated Learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

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Observation 8d6546df-a5ba-48e5-8b66-56cd8f1d51e5 · outbound

This paper cites Improving the model consistency of decentralized federated learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Improving the model consistency of decentralized federated learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.140941Z

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Observation d0feb1a1-c2db-4d14-953f-6d3ce05070c3 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 49

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Observation 918ae78b-912e-4ab0-8b3c-c39591c564a3 · outbound

This paper cites Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T21:32:12.934059Z

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Observation 1d0f1e02-942e-459e-a067-745b18676b4f · outbound

This paper cites HyperbolicLR: Epoch insensitive learning rate scheduler.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning HyperbolicLR: Epoch insensitive learning rate scheduler

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T21:32:12.938781Z

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Observation df980248-0be2-43b0-91e5-53930d5df80d · outbound

This paper cites FedMMD: A Federated weighting algorithm consideringNon-IIDandLocalModelDeviation.ExpertSystemswith Applications, 237:121463, 2024.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedMMD: A Federated weighting algorithm consideringNon-IIDandLocalModelDeviation.ExpertSystemswith Applications, 237:121463, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.122110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48585ab9-2a99-48c3-888d-9c8f7243b30d · outbound

This paper cites Personalized federated learning via deviation tracking representation learning.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Personalized federated learning via deviation tracking representation learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.104045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5d571a4b-0d71-48bc-9832-7e464b8ccb77 · outbound

This paper cites FedRDA: Representation Deviation Alignment in Heterogeneous Federated Learning.IEEE Transactions on Industrial Informatics, 2025.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning FedRDA: Representation Deviation Alignment in Heterogeneous Federated Learning.IEEE Transactions on Industrial Informatics, 2025

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:32:14.087276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 42525426-de57-424f-bae4-0deae586cf63 · outbound

This paper cites doi:https://doi.org/10.1016/j.ins.2023.01.130.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning doi:https://doi.org/10.1016/j.ins.2023.01.130

Reference 2023

Resolution: verified exact; doi, observed 2026-08-11T21:32:12.991691Z

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Observation 120fefd8-0df4-47f2-b92e-565f7ee74f2f · outbound

This paper cites an unresolved cited work.

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T21:32:12.726182Z

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