Paper Citation Record · LEDGER

One-shot Federated Learning Methods: A Practical Guide

As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2502.09104.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.09104 v1

Coverage vector

measured 54 of 54 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: arxiv_reference, observed 2026-05-10T14:20:29.463175Z

Reference resolution

54 of 54 outbound references displayed

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External citation measurements

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Outbound references

Observation 01ca1550-226d-4993-94e5-5d227834650b · outbound

This paper cites Rfclock: Timing, phase and frequency synchroniza- tion for distributed wireless networks.

One-shot Federated Learning Methods: A Practical Guide Rfclock: Timing, phase and frequency synchroniza- tion for distributed wireless networks

Reference 1

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This paper cites Practical secure aggregation for privacy-preservin g machine learning.

One-shot Federated Learning Methods: A Practical Guide Practical secure aggregation for privacy-preservin g machine learning

Reference 4

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This paper cites Homomorphic encryption for arithmetic of approximate numbers.

One-shot Federated Learning Methods: A Practical Guide Homomorphic encryption for arithmetic of approximate numbers

Reference 6

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This paper cites Enhancing one- shot federated learning through data and ensemble co- boosting.

One-shot Federated Learning Methods: A Practical Guide Enhancing one- shot federated learning through data and ensemble co- boosting

Reference 7

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This paper cites Heterogeneity for the win: One-shot feder- ated clustering.

One-shot Federated Learning Methods: A Practical Guide Heterogeneity for the win: One-shot feder- ated clustering

Reference 8

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This paper cites Heteroﬂ: Computation and communication efﬁcient feder- ated learning for heterogeneous clients.

One-shot Federated Learning Methods: A Practical Guide Heteroﬂ: Computation and communication efﬁcient feder- ated learning for heterogeneous clients

Reference 9

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This paper cites Towards addressing label skews in one-shot federated learning.

One-shot Federated Learning Methods: A Practical Guide Towards addressing label skews in one-shot federated learning

Reference 10

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This paper cites One-Shot Federated Learning.

One-shot Federated Learning Methods: A Practical Guide One-Shot Federated Learning

Reference 14

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This paper cites Data-free one-shot federated learning un - der very high statistical heterogeneity.

One-shot Federated Learning Methods: A Practical Guide Data-free one-shot federated learning un - der very high statistical heterogeneity

Reference 17

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This paper cites Practical hybrid gradient compression for federated learn - ing systems.

One-shot Federated Learning Methods: A Practical Guide Practical hybrid gradient compression for federated learn - ing systems

Reference 18

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This paper cites One-shot federated conformal prediction.

One-shot Federated Learning Methods: A Practical Guide One-shot federated conformal prediction

Reference 19

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This paper cites Adaptive mix- tures of local experts.

One-shot Federated Learning Methods: A Practical Guide Adaptive mix- tures of local experts

Reference 20

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This paper cites Oﬂ-w3: A one-shot federated learning system on web 3.0.

One-shot Federated Learning Methods: A Practical Guide Oﬂ-w3: A one-shot federated learning system on web 3.0

Reference 22

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This paper cites Advances and open problems in federated learning.

One-shot Federated Learning Methods: A Practical Guide Advances and open problems in federated learning

Reference 23

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This paper cites One-shot federated learning on medi- cal data using knowledge distillation with image synthesis and client model adaptation.

One-shot Federated Learning Methods: A Practical Guide One-shot federated learning on medi- cal data using knowledge distillation with image synthesis and client model adaptation

Reference 24

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This paper cites Scaffold: Stochastic controlled averaging for federated learning.

One-shot Federated Learning Methods: A Practical Guide Scaffold: Stochastic controlled averaging for federated learning

Reference 25

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This paper cites Osgan: One-shot distributed learning using generative adversari al networks.

One-shot Federated Learning Methods: A Practical Guide Osgan: One-shot distributed learning using generative adversari al networks

Reference 27

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This paper cites Mediator: Memory-efﬁcient llm merging with less parameter conﬂicts and uncertainty based routing.

One-shot Federated Learning Methods: A Practical Guide Mediator: Memory-efﬁcient llm merging with less parameter conﬂicts and uncertainty based routing

Reference 28

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This paper cites Federated optimization in heterogeneous networks.

One-shot Federated Learning Methods: A Practical Guide Federated optimization in heterogeneous networks

Reference 29

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This paper cites Federated learning on non-iid data silos: An experimental study.

One-shot Federated Learning Methods: A Practical Guide Federated learning on non-iid data silos: An experimental study

Reference 30

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This paper cites Accel- erate one-shot federated learning through ensemble opti- mization.

One-shot Federated Learning Methods: A Practical Guide Accel- erate one-shot federated learning through ensemble opti- mization

Reference 31

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This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

One-shot Federated Learning Methods: A Practical Guide Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 32

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One-shot Federated Learning Methods: A Practical Guide FedTMOS: Efﬁcient one-shot federated learning with tsetlin machine

Reference 34

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This paper cites Learning transferable visual models from natural language supervision.

One-shot Federated Learning Methods: A Practical Guide Learning transferable visual models from natural language supervision

Reference 35

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One-shot Federated Learning Methods: A Practical Guide High-resolution image synthesis with latent diffusion models

Reference 36

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One-shot Federated Learning Methods: A Practical Guide Unresolved cited work

Reference 37

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This paper cites Bridging general and personalized federated learning through selec - tive model integration.

One-shot Federated Learning Methods: A Practical Guide Bridging general and personalized federated learning through selec - tive model integration

Reference 38

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This paper cites XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning.

One-shot Federated Learning Methods: A Practical Guide XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning

Reference 39

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One-shot Federated Learning Methods: A Practical Guide Ef- fective heterogeneous federated learning via efﬁcient hypernetwork-based weight generation

Reference 40

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One-shot Federated Learning Methods: A Practical Guide Federated multi-task learning

Reference 41

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This paper cites Proto- typical networks for few-shot learning.

One-shot Federated Learning Methods: A Practical Guide Proto- typical networks for few-shot learning

Reference 42

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This paper cites Federated learning via decentralized dataset distillation in resour ce- constrained edge environments.

One-shot Federated Learning Methods: A Practical Guide Federated learning via decentralized dataset distillation in resour ce- constrained edge environments

Reference 43

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One-shot Federated Learning Methods: A Practical Guide One-shot federated learning without server-side training

Reference 44

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One-shot Federated Learning Methods: A Practical Guide Virtual homogeneity learning: Defend- ing against data heterogeneity in federated learning

Reference 45

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One-shot Federated Learning Methods: A Practical Guide Federated learning with matched averaging

Reference 46

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This paper cites Data-free diversity-based ensemble selection for one-shot federate d learning.

One-shot Federated Learning Methods: A Practical Guide Data-free diversity-based ensemble selection for one-shot federate d learning

Reference 47

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This paper cites Mixture-of-Agents Enhances Large Language Model Capabilities.

One-shot Federated Learning Methods: A Practical Guide Mixture-of-Agents Enhances Large Language Model Capabilities

Reference 48

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This paper cites A survey on efﬁcient federated learning methods for foundation model training.

One-shot Federated Learning Methods: A Practical Guide A survey on efﬁcient federated learning methods for foundation model training

Reference 49

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This paper cites Open- fedllm: Training large language models on decentralized private data via federated learning.

One-shot Federated Learning Methods: A Practical Guide Open- fedllm: Training large language models on decentralized private data via federated learning

Reference 50

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This paper cites Bayesian nonparametric federated learning of neural networks.

One-shot Federated Learning Methods: A Practical Guide Bayesian nonparametric federated learning of neural networks

Reference 51

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One-shot Federated Learning Methods: A Practical Guide One-shot- but-not-degraded federated learning

Reference 52

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This paper cites Dense: Data-free one-shot federated learning.

One-shot Federated Learning Methods: A Practical Guide Dense: Data-free one-shot federated learning

Reference 53

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This paper cites Distilled One-Shot Federated Learning.

One-shot Federated Learning Methods: A Practical Guide Distilled One-Shot Federated Learning

Reference 54

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This paper cites Towards a theoretical and practical understanding of one-shot federated learnin g with ﬁsher information.

One-shot Federated Learning Methods: A Practical Guide Towards a theoretical and practical understanding of one-shot federated learnin g with ﬁsher information

Reference 1991

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This paper cites Preserving privacy in federated learning with ensemble cross-domain knowledge distillation.

One-shot Federated Learning Methods: A Practical Guide Preserving privacy in federated learning with ensemble cross-domain knowledge distillation

Reference 2011

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Observation 4e1d6352-883e-4c3e-8a38-c690bba571ff · outbound

This paper cites Knowledge distillation for fed - erated learning: a practical guide.

One-shot Federated Learning Methods: A Practical Guide Knowledge distillation for fed - erated learning: a practical guide

Reference 2016

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This paper cites FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models.

One-shot Federated Learning Methods: A Practical Guide FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models

Reference 2017

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This paper cites Exploring one-shot federated learning by model inversion and token relabel with vision transformers,.

One-shot Federated Learning Methods: A Practical Guide Exploring one-shot federated learning by model inversion and token relabel with vision transformers,

Reference 2019

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Observation 7f4c6e14-0caa-4520-a22f-ff9768e12e74 · outbound

This paper cites Fusion learning: A one shot feder- ated learning.

One-shot Federated Learning Methods: A Practical Guide Fusion learning: A one shot feder- ated learning

Reference 2020

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This paper cites Revisiting ensembling in one-shot federated learn- ing.

One-shot Federated Learning Methods: A Practical Guide Revisiting ensembling in one-shot federated learn- ing

Reference 2021

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This paper cites MiniLLM: Knowledge distillation of large language models.

One-shot Federated Learning Methods: A Practical Guide MiniLLM: Knowledge distillation of large language models

Reference 2022

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Observation c14d3eae-54fe-4ddc-9ee5-5acd68b9b94c · outbound

This paper cites Differential privacy.

One-shot Federated Learning Methods: A Practical Guide Differential privacy

Reference 2023

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This paper cites Parametric Feature Transfer: One-shot Federated Learning with Foundation Models.

One-shot Federated Learning Methods: A Practical Guide Parametric Feature Transfer: One-shot Federated Learning with Foundation Models

Reference 2024

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This paper cites Calibrated one round federated learning with bayesian inference in the predic- tive space.

One-shot Federated Learning Methods: A Practical Guide Calibrated one round federated learning with bayesian inference in the predic- tive space

Reference 2025

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Pith citing papers

Observation 86343c57-7e41-418c-9ceb-f5538e11fea9 · inbound

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction cites this paper.

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction One-shot Federated Learning Methods: A Practical Guide

Reference 33

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