Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning | Paper Citation Record

Observation 59774571-1fc3-440c-a0b1-f6cb5eec3195 · outbound

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

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Communication-efficient learning of deep networks from decentralized data,

Reference 1

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This paper cites Trading off privacy, utility, and efficiency in federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Trading off privacy, utility, and efficiency in federated learning,

Reference 2

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This paper cites Cross-silo prototypical calibration for federated learning with non-iid data,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Cross-silo prototypical calibration for federated learning with non-iid data,

Reference 3

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This paper cites Rethinking architecture design for tackling data heterogeneity in federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Rethinking architecture design for tackling data heterogeneity in federated learning,

Reference 4

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This paper cites Fedfed: Feature distillation against data heterogeneity in federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Fedfed: Feature distillation against data heterogeneity in federated learning,

Reference 5

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This paper cites Towards efficient replay in federated incremental learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Towards efficient replay in federated incremental learning,

Reference 6

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This paper cites Cross-silo feature space alignment for federated learning on clients with imbalanced data,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Cross-silo feature space alignment for federated learning on clients with imbalanced data,

Reference 7

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Observation ccea0f49-7df1-46ae-850a-e1b1c5681ba5 · outbound

This paper cites Personalized federated domain-incremental learning based on adaptive knowledge matching,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Personalized federated domain-incremental learning based on adaptive knowledge matching,

Reference 8

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Observation 99cd61a7-5004-4bef-b6d4-105706e919e8 · outbound

This paper cites Ditto fair and robust federated learning through personalization,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Ditto fair and robust federated learning through personalization,

Reference 9

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Observation ac764c92-cac3-4828-9132-7fa75282952d · outbound

This paper cites How to prevent the poor performance clients for personalized federated learning?.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning How to prevent the poor performance clients for personalized federated learning?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.374446Z

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Observation a180e182-f3b5-4d6c-903a-0242f4146f83 · outbound

This paper cites On Bridging Generic and Personalized Federated Learning for Image Classification.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning On Bridging Generic and Personalized Federated Learning for Image Classification

Reference 11

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Observation 0878b81f-4fcc-4729-b18b-ba6548bd7108 · outbound

This paper cites Exploiting shared representations for personalized federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Exploiting shared representations for personalized federated learning,

Reference 12

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Observation 64ee6665-5885-42ee-94d9-375f3b4d9682 · outbound

This paper cites FedBABU: Towards Enhanced Representation for Federated Image Classification.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning FedBABU: Towards Enhanced Representation for Federated Image Classification

Reference 13

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Observation f89a3be3-4af8-4f37-9bd7-75af270d5469 · outbound

This paper cites Fedcp: Separating feature information for personalized federated learning via conditional policy,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Fedcp: Separating feature information for personalized federated learning via conditional policy,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.339021Z

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Observation bcbdb60c-42db-429a-bdd5-67179b44c766 · outbound

This paper cites Perada: Parameter-efficient federated learning personalization with generalization guarantees,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Perada: Parameter-efficient federated learning personalization with generalization guarantees,

Reference 15

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Observation a847da49-5759-4a80-8ad6-b4e0aa1be1b4 · outbound

This paper cites Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training,

Reference 16

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Observation e5a38d9e-2281-4aaf-95e5-b7743ac43822 · outbound

This paper cites On the effectiveness of partial variance reduction in federated learning with heterogeneous data,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning On the effectiveness of partial variance reduction in federated learning with heterogeneous data,

Reference 17

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Observation 64c8536e-534b-404e-b667-7243598c3808 · outbound

This paper cites Decentralized directed collaboration for personalized federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Decentralized directed collaboration for personalized federated learning,

Reference 18

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Observation 722317c3-1b95-44fd-9dd0-68fa100a5a88 · outbound

This paper cites Advances and open problems in federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Advances and open problems in federated learning,

Reference 19

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Observation 9299ac64-c454-4c87-b263-566faa3b79dd · outbound

This paper cites Learning to collaborate in decentralized learning of personalized models,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learning to collaborate in decentralized learning of personalized models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.226723Z

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Observation ff83d49c-6783-4edc-b1c9-a7812c5ee2fc · outbound

This paper cites Personalized decentralized federated learning with knowledge distillation,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Personalized decentralized federated learning with knowledge distillation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.207478Z

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Observation fea5c71b-486f-498d-900d-074f8f6c58b8 · outbound

This paper cites Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey

Reference 22

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This paper cites Learngene from open-world to your learning task,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learngene from open-world to your learning task,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.189763Z

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Observation 14e79b3a-7676-4a10-b89b-f44b3b13a1bd · outbound

This paper cites Learngene: Inheriting Condensed Knowledge from the Ancestry Model to Descendant Models.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learngene: Inheriting Condensed Knowledge from the Ancestry Model to Descendant Models

Reference 24

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This paper cites Initializing variable-sized vision transformers from learngene with learnable transformation,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Initializing variable-sized vision transformers from learngene with learnable transformation,

Reference 25

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This paper cites Learn from others and be yourself in heterogeneous federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learn from others and be yourself in heterogeneous federated learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.154729Z

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Observation c1b67b53-333e-483a-a770-58d70f8d6ab9 · outbound

This paper cites Fedproto federated prototype learning across heterogeneous clients,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Fedproto federated prototype learning across heterogeneous clients,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.139151Z

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This paper cites Fedtgp: Trainable global prototypes with adaptive-margin-enhanced contrastive learning for data and model heterogeneity in federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Fedtgp: Trainable global prototypes with adaptive-margin-enhanced contrastive learning for data and model heterogeneity in federated learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.123167Z

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This paper cites Recovering Labels from Local Updates in Federated Learning.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Recovering Labels from Local Updates in Federated Learning

Reference 29

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This paper cites Decentralized federated learning: Balancing communication and computing costs,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Decentralized federated learning: Balancing communication and computing costs,

Reference 30

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Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Decentralized federated averaging,

Reference 31

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This paper cites Disentangled representation learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Disentangled representation learning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.084883Z

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This paper cites Commutative lie group vae for disentanglement learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Commutative lie group vae for disentanglement learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.067545Z

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Observation 573d4aee-68b0-48c8-9fbf-9342904b24ea · outbound

This paper cites Dualvae: Dual disentangled variational autoencoder for recommendation,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Dualvae: Dual disentangled variational autoencoder for recommendation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.052263Z

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This paper cites Auto-Encoding Variational Bayes.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Auto-Encoding Variational Bayes

Reference 35

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Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learning structured output representation using deep conditional generative models,

Reference 36

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Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Personalization disentanglement for federated learning,

Reference 37

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This paper cites Disentangled federated learning for tackling attributes skew via invariant aggregation and diversity transferring,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Disentangled federated learning for tackling attributes skew via invariant aggregation and diversity transferring,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:34.002448Z

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This paper cites On disentanglement of asymmetrical knowledge transfer for modality-task agnostic federated learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning On disentanglement of asymmetrical knowledge transfer for modality-task agnostic federated learning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.986311Z

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This paper cites Spatio-temporal heterogeneous federated learning for time series classification with multi-view orthogonal training,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Spatio-temporal heterogeneous federated learning for time series classification with multi-view orthogonal training,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.966357Z

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This paper cites Linearly decomposing and recomposing vision transformers for diverse-scale models,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Linearly decomposing and recomposing vision transformers for diverse-scale models,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.949292Z

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Observation 2302ca51-0d4f-42e0-bfce-89d433ebb1ba · outbound

This paper cites Transformer as linear expansion of learngene,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Transformer as linear expansion of learngene,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.933345Z

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Observation 56576fbe-24d9-40f8-8b8e-7ae7cd52d536 · outbound

This paper cites Vision transformers as probabilistic expansion from learngene,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Vision transformers as probabilistic expansion from learngene,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.918742Z

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This paper cites Facilitating ai-based csi feedback deployment in massive mimo systems with learngene,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Facilitating ai-based csi feedback deployment in massive mimo systems with learngene,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.903565Z

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Observation ccb0609b-dbb3-4f96-b16a-78222aebada9 · outbound

This paper cites WAVE: Weight Templates for Adaptive Initialization of Variable-sized Models.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning WAVE: Weight Templates for Adaptive Initialization of Variable-sized Models

Reference 45

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This paper cites KIND: Knowledge Integration and Diversion for Training Decomposable Models.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning KIND: Knowledge Integration and Diversion for Training Decomposable Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.295230Z

Source-reported events for the cited work

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Observation 545c56df-4219-46ec-950b-215454ac3ef4 · outbound

This paper cites Building variable-sized models via learngene pool,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Building variable-sized models via learngene pool,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.887431Z

Source-reported events for the cited work

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Observation 0c23c87f-270b-4234-bcfe-2fceaf8788eb · outbound

This paper cites Transferring Core Knowledge via Learngenes.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Transferring Core Knowledge via Learngenes

Reference 48

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This paper cites Rethinking feature distribution for loss functions in image classification,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Rethinking feature distribution for loss functions in image classification,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.870538Z

Source-reported events for the cited work

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Observation ad44ffc9-d3d0-4624-bf12-e42c02b0122f · outbound

This paper cites Disentangling latent space for vae by label relevant/irrelevant dimensions,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Disentangling latent space for vae by label relevant/irrelevant dimensions,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.854390Z

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This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Infogan: Interpretable representation learning by information maximizing generative adversarial nets,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.839120Z

Source-reported events for the cited work

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Observation 718ecebe-af74-4ff3-834b-bee68b27e94a · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Reading digits in natural images with unsupervised feature learning,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.822818Z

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Observation 36fcffa2-ae5a-44ab-86c6-cdb167f98a6b · outbound

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

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Learning multiple layers of features from tiny images,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.804338Z

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Observation f9ac7835-3bdb-4329-8981-3686e9313271 · outbound

This paper cites Communication efficient primal-dual algorithm for nonconvex nonsmooth distributed optimization,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Communication efficient primal-dual algorithm for nonconvex nonsmooth distributed optimization,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.788368Z

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Observation 3da22367-ebb1-4fae-8cbb-8653735275bd · outbound

This paper cites Tackling the objective inconsistency problem in heterogeneous federated optimization,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Tackling the objective inconsistency problem in heterogeneous federated optimization,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.771208Z

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Observation 67fd562b-c7be-4c4a-8913-697874771a0c · outbound

This paper cites FedBN: Federated Learning on Non-IID Features via Local Batch Normalization.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.345817Z

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Observation bdd11466-3eab-484e-9560-d0794b39371a · outbound

This paper cites A generalized fractionally integrated autoregressive moving-average process,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning A generalized fractionally integrated autoregressive moving-average process,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.750729Z

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Observation 9ff19dee-69e1-4ddd-993c-14e5040764c7 · outbound

This paper cites Following a trend with an exponential moving average: Analytical results for a gaussian model,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Following a trend with an exponential moving average: Analytical results for a gaussian model,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.733653Z

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Observation 54abdb3b-7f3d-4eb6-a052-16266ae6a4d1 · outbound

This paper cites Addressing skewed heterogeneity via federated prototype rectification with personalization,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Addressing skewed heterogeneity via federated prototype rectification with personalization,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.714628Z

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Observation 14460756-dbe1-4aed-baa2-58810523e660 · outbound

This paper cites A unified federated learning framework for wireless communications: Towards privacy, efficiency, and security,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning A unified federated learning framework for wireless communications: Towards privacy, efficiency, and security,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.697806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 813effc3-5581-4eda-b2ec-47990c27c5ba · outbound

This paper cites Detecting malicious model updates from federated learning on conditional variational autoencoder,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Detecting malicious model updates from federated learning on conditional variational autoencoder,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.681061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 07bd29e2-7af5-426c-878d-be7093de1bf9 · outbound

This paper cites Data-free one-shot federated learning under very high statistical heterogeneity,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Data-free one-shot federated learning under very high statistical heterogeneity,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.373685Z

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Observation 2c48e828-0140-409d-b97c-874de3133c34 · outbound

This paper cites Communication efficient distributed learning using variational auto encoders,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Communication efficient distributed learning using variational auto encoders,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:07:33.652031Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 384811a0-1ba3-4dea-be53-860c378455b5 · outbound

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

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.383915Z

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Observation c039b7f9-1fd1-4c1f-a8eb-79d0d818b5b0 · outbound

This paper cites Deep leakage from gradients,.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning Deep leakage from gradients,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.388485Z

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Observation 9c28bf09-c565-440d-aa9f-b0958fe72ad3 · outbound

This paper cites pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning.

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:33.393186Z

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