FedMD: Heterogenous Federated Learning via Model Distillation | Paper Citation Record

Observation 6eef8430-eeeb-45b2-9d24-bbd5fda3085b · inbound

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions cites this paper.

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions FedMD: Heterogenous Federated Learning via Model Distillation

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:48:39.297162Z

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Observation 0a37434d-c1a8-4b95-9de3-5fe96e3b9000 · inbound

Federated Knowledge Distillation for Multi-Model Architectures Lithography Hotspot Detection cites this paper.

Federated Knowledge Distillation for Multi-Model Architectures Lithography Hotspot Detection FedMD: Heterogenous Federated Learning via Model Distillation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:42:36.313437Z

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Data Overvaluation Attack and Truthful Data Valuation in Federated Learning cites this paper.

Data Overvaluation Attack and Truthful Data Valuation in Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 18

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FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation cites this paper.

FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 23

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Interaction-Aware Gaussian Weighting for Clustered Federated Learning cites this paper.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 1998

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Observation 3a25adac-4864-4777-b8cb-5ebe32aacbf3 · inbound

Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation cites this paper.

Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 22

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FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices cites this paper.

FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices FedMD: Heterogenous Federated Learning via Model Distillation

Reference 38

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Observation b7d12fd9-c9ff-43f3-83a1-c3e69fa548dc · inbound

Federated Learning-Distillation Alternation for Resource-Constrained IoT cites this paper.

Federated Learning-Distillation Alternation for Resource-Constrained IoT FedMD: Heterogenous Federated Learning via Model Distillation

Reference 25

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Observation c437739f-4c3e-4780-b3e2-6ada7878efc0 · inbound

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data cites this paper.

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data FedMD: Heterogenous Federated Learning via Model Distillation

Reference 24

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Observation 463ffae0-8d4a-4741-8688-57a4af3a6b49 · inbound

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms cites this paper.

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms FedMD: Heterogenous Federated Learning via Model Distillation

Reference 79

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Observation 0c833a7a-7c81-4444-95f5-b1f4b7f12ec0 · inbound

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks cites this paper.

SEMFED: Semantic-Aware Resource-Efficient Federated Learning for Heterogeneous NLP Tasks FedMD: Heterogenous Federated Learning via Model Distillation

Reference 21

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Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions cites this paper.

Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions FedMD: Heterogenous Federated Learning via Model Distillation

Reference 1998

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Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation cites this paper.

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 30

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Observation 2e010ee3-a1d7-4bb3-b496-955547203c8e · inbound

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data cites this paper.

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data FedMD: Heterogenous Federated Learning via Model Distillation

Reference 25

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Observation e8a084e9-06b3-4303-9b2a-9a1b910f8c3f · inbound

Heterogeneous Federated Learning with Prototype Alignment and Upscaling cites this paper.

Heterogeneous Federated Learning with Prototype Alignment and Upscaling FedMD: Heterogenous Federated Learning via Model Distillation

Reference 15

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TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments cites this paper.

TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments FedMD: Heterogenous Federated Learning via Model Distillation

Reference 12

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Hypernetworks for Model-Heterogeneous Personalized Federated Learning cites this paper.

Hypernetworks for Model-Heterogeneous Personalized Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 18

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Observation 8a212164-63e4-45b9-a13b-1d148c7c1299 · inbound

Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer cites this paper.

Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer FedMD: Heterogenous Federated Learning via Model Distillation

Reference 21

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Heterogeneity-Oblivious Robust Federated Learning cites this paper.

Heterogeneity-Oblivious Robust Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 18

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Observation 8b14e4cf-5666-4081-8552-73745ff23761 · inbound

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models cites this paper.

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models FedMD: Heterogenous Federated Learning via Model Distillation

Reference 26

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Observation 3c3b7dfe-71b1-4bfa-9bc0-ede69c42e1f1 · inbound

Generalizable Federated Learning using Client Adaptive Focal Modulation cites this paper.

Generalizable Federated Learning using Client Adaptive Focal Modulation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 34

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Observation 0b63a6ff-67ea-442f-9709-cdf69aed56eb · inbound

Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks cites this paper.

Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks FedMD: Heterogenous Federated Learning via Model Distillation

Reference 6

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Observation 061b6739-b7d5-4e3e-8a3f-0642c3cccd0a · inbound

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization cites this paper.

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization FedMD: Heterogenous Federated Learning via Model Distillation

Reference 128

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Observation 4d06c913-0d1c-4f77-9384-64b44fa79d5f · inbound

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion cites this paper.

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion FedMD: Heterogenous Federated Learning via Model Distillation

Reference 80

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Observation 9cb440be-5b8c-4518-a633-e11c61adf73f · inbound

When To Adapt? Adapting the Model or Data in Federated Medical Imaging cites this paper.

When To Adapt? Adapting the Model or Data in Federated Medical Imaging FedMD: Heterogenous Federated Learning via Model Distillation

Reference 16

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Observation afd47aca-a379-40af-bbd1-84908542c82d · inbound

Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning cites this paper.

Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:01:06.511126Z

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Observation 1cddeaa6-b3fc-435e-94c1-cd0e412c99f1 · inbound

From Coordinate Matching to Structural Alignment: Rethinking Prototype Alignment in Heterogeneous Federated Learning cites this paper.

From Coordinate Matching to Structural Alignment: Rethinking Prototype Alignment in Heterogeneous Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:51:10.792471Z

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Observation 92a3f5fe-75a9-4538-a91b-cbaca25bbdb6 · inbound

HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning cites this paper.

HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:45:58.341487Z

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Observation 44dc985e-03ae-4c43-b3c9-c6752abfa761 · inbound

Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective cites this paper.

Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective FedMD: Heterogenous Federated Learning via Model Distillation

Reference 29

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Observation 99c2508c-2361-4cc8-a2f7-11c72a4ed7a3 · inbound

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication cites this paper.

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication FedMD: Heterogenous Federated Learning via Model Distillation

Reference 16

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Observation 3e2a5bc9-3624-46ce-8455-88922f09b987 · inbound

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication cites this paper.

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication FedMD: Heterogenous Federated Learning via Model Distillation

Reference 16

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Observation 6612cef7-9c9a-42eb-b06c-93864695a54e · inbound

On What We Can Learn from Low-Resolution Data cites this paper.

On What We Can Learn from Low-Resolution Data FedMD: Heterogenous Federated Learning via Model Distillation

Reference 31

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Observation ad3dc307-8aa2-4e43-9c96-93193e34c76a · inbound

BiFedKD: Bidirectional Federated Knowledge Distillation Framework for Non-IID and Long-Tailed ECG Monitoring cites this paper.

BiFedKD: Bidirectional Federated Knowledge Distillation Framework for Non-IID and Long-Tailed ECG Monitoring FedMD: Heterogenous Federated Learning via Model Distillation

Reference 9

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Observation 71cd7a9e-cf93-4a85-99c3-89a4d7c045a5 · inbound

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning cites this paper.

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 12

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Observation b38888b5-99e4-4617-a529-d90052e3842a · inbound

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning cites this paper.

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 6

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Observation 71ab4c0b-e763-4d6a-8d2a-23019047f915 · inbound

FedMTFI: Feature Importance Based Optimized Multi Teacher Knowledge Distillation in Heterogeneous Federated Learning Environment cites this paper.

FedMTFI: Feature Importance Based Optimized Multi Teacher Knowledge Distillation in Heterogeneous Federated Learning Environment FedMD: Heterogenous Federated Learning via Model Distillation

Reference 18

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Observation 50f42fd3-230c-4a32-9515-393dbffc8b7a · inbound

Efficient Federated Estimation and Inference for High-Dimensional Tail Index Regression cites this paper.

Efficient Federated Estimation and Inference for High-Dimensional Tail Index Regression FedMD: Heterogenous Federated Learning via Model Distillation

Reference 4

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Observation 77276518-85ba-4c02-b758-bbfff9f55270 · inbound

HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning cites this paper.

HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 24

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Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning cites this paper.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 23

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Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning cites this paper.

Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:07:29.737905Z

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Observation 55cb39bc-79af-40a4-a6c2-1f36cf9b7a74 · inbound

Asynchronous Decentralized Federated Learning over Lossy Wireless Links via Reception- and Age-Aware Aggregation cites this paper.

Asynchronous Decentralized Federated Learning over Lossy Wireless Links via Reception- and Age-Aware Aggregation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:17:37.618898Z

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Observation 9ec1d695-e28d-458d-bccd-7358d602fb49 · inbound

Tuning-Free Efficient Estimation for Multi-Source Data via Covariance-Aware Shrinkage cites this paper.

Tuning-Free Efficient Estimation for Multi-Source Data via Covariance-Aware Shrinkage FedMD: Heterogenous Federated Learning via Model Distillation

Reference 125

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T16:44:56.438631Z

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Observation 35ba51d8-61e9-4018-8d08-18c5dd1f19c2 · inbound

TallyTrain: Communication-Efficient Federated Distillation cites this paper.

TallyTrain: Communication-Efficient Federated Distillation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 2

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Observation 111293dd-bedd-4e71-96de-4b48d9469316 · inbound

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems cites this paper.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems FedMD: Heterogenous Federated Learning via Model Distillation

Reference 9

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Observation 433e6942-168b-4133-9aa1-3e56899999b5 · inbound

Federated Lightweight Fine-Tuning cites this paper.

Federated Lightweight Fine-Tuning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 15

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Observation 6adb613a-878a-4f93-9bd0-8b9e394f0dd0 · inbound

Autonomous Collaborative Learning Among an Ensemble of Tsetlin Machines with Consensus-Based Inference cites this paper.

Autonomous Collaborative Learning Among an Ensemble of Tsetlin Machines with Consensus-Based Inference FedMD: Heterogenous Federated Learning via Model Distillation

Reference 32

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Observation 479b3c50-4af9-462a-91b9-35a430cea43d · inbound

FedTopo: Relation-Level Topology Sharing for Model-Heterogeneous Federated Learning cites this paper.

FedTopo: Relation-Level Topology Sharing for Model-Heterogeneous Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 8

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Observation 1c5d94b1-a5e4-4c83-9aa8-f6e991fd898f · inbound

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning cites this paper.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 14

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AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning cites this paper.

AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 22

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