Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity | Paper Citation Record

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This paper cites Federated Residual Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Residual Learning

Reference 1

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This paper cites Federated Learning with Personalization Layers.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Learning with Personalization Layers

Reference 2

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This paper cites Revisiting sparsity hunting in federated learning: Why does sparsity consensus matter? Transactions on Machine Learning Research, 2023.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Revisiting sparsity hunting in federated learning: Why does sparsity consensus matter? Transactions on Machine Learning Research, 2023

Reference 3

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This paper cites Federated dynamic sparse training: Computing less, communicating less, yet learning better.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated dynamic sparse training: Computing less, communicating less, yet learning better

Reference 4

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This paper cites Efficient personalized federated learning via sparse model-adaptation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Efficient personalized federated learning via sparse model-adaptation

Reference 5

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This paper cites Sparsity winning twice: Better robust generalization from more efficient training.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Sparsity winning twice: Better robust generalization from more efficient training

Reference 6

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This paper cites Streamlining redundant layers to compress large language models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Streamlining redundant layers to compress large language models

Reference 7

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This paper cites Exploiting shared representations for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Exploiting shared representations for personalized federated learning

Reference 8

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Observation cfd3b0d8-01f1-4add-b9c4-f606d2b9705e · outbound

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training

Reference 9

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This paper cites Flexible clustered federated learning for client-level data distribution shift.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Flexible clustered federated learning for client-level data distribution shift

Reference 10

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This paper cites Rigging the lottery: Making all tickets winners.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Rigging the lottery: Making all tickets winners

Reference 11

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Observation ba925d77-4cd8-41c0-acb1-327624e235b9 · outbound

This paper cites Gradient flow in sparse neural networks and how lottery tickets win.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Gradient flow in sparse neural networks and how lottery tickets win

Reference 12

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This paper cites An efficient framework for clustered federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity An efficient framework for clustered federated learning

Reference 13

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This paper cites The unreasonable ineffectiveness of the deeper layers.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity The unreasonable ineffectiveness of the deeper layers

Reference 14

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This paper cites Adaptive gradient sparsification for efficient federated learning: An online learning approach.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Adaptive gradient sparsification for efficient federated learning: An online learning approach

Reference 15

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This paper cites Deep residual learning for image recognition.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Deep residual learning for image recognition

Reference 16

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This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 17

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This paper cites Achieving Personalized Federated Learning with Sparse Local Models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Achieving Personalized Federated Learning with Sparse Local Models

Reference 18

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This paper cites Federated learning via meta-variational dropout.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning via meta-variational dropout

Reference 19

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Observation bd7b1744-7e11-4eae-aaf9-42b54c07da37 · outbound

This paper cites Tracing representation progression: Analyzing and enhancing layer-wise similarity.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Tracing representation progression: Analyzing and enhancing layer-wise similarity

Reference 20

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This paper cites Complement sparsification: Low-overhead model pruning for federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Complement sparsification: Low-overhead model pruning for federated learning

Reference 21

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This paper cites Improving Federated Learning Personalization via Model Agnostic Meta Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 22

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This paper cites Model pruning enables efficient federated learning on edge devices.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Model pruning enables efficient federated learning on edge devices

Reference 23

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This paper cites Personalized edge intelligence via federated self-knowledge distillation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Personalized edge intelligence via federated self-knowledge distillation

Reference 24

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Scaffold: Stochastic controlled averaging for federated learning

Reference 25

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Learning multiple layers of features from tiny images

Reference 26

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This paper cites Cifar-10 (canadian institute for advanced research).

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Cifar-10 (canadian institute for advanced research)

Reference 27

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This paper cites Federated LoRA with Sparse Communication.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated LoRA with Sparse Communication

Reference 28

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This paper cites Tiny imagenet visual recognition challenge.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Tiny imagenet visual recognition challenge

Reference 29

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This paper cites Preservation of the global knowledge by not-true distillation in federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Preservation of the global knowledge by not-true distillation in federated learning

Reference 30

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Snip: single-shot network pruning based on connection sensitivity

Reference 31

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This paper cites Lotteryfl: Empower edge intelligence with personalized and communication-efficient federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Lotteryfl: Empower edge intelligence with personalized and communication-efficient federated learning

Reference 32

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning on non-iid data silos: An experimental study

Reference 33

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated optimization in heterogeneous networks

Reference 34

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This paper cites Ditto: Fair and robust federated learning through personalization.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Ditto: Fair and robust federated learning through personalization

Reference 35

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedbn: Federated learning on non-iid features via local batch normalization

Reference 36

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Ensemble distillation for robust model fusion in federated learning

Reference 37

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity

Reference 38

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This paper cites Federated learning for open banking.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning for open banking

Reference 39

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This paper cites Data-aware gradient compression for fl in communication-constrained mobile computing.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Data-aware gradient compression for fl in communication-constrained mobile computing

Reference 40

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Observation 1b374ad0-f8b7-46a6-a377-13ecd2cd6d68 · outbound

This paper cites Layer-wised model aggregation for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Layer-wised model aggregation for personalized federated learning

Reference 41

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Observation 94ff3aa7-7dd1-4983-9dbc-1690f71e98c2 · outbound

This paper cites Three Approaches for Personalization with Applications to Federated Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Three Approaches for Personalization with Applications to Federated Learning

Reference 42

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Communication-efficient learning of deep networks from decentralized data

Reference 43

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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 44

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This paper cites DOCS : Quantifying weight similarity for deeper insights into large language models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity DOCS : Quantifying weight similarity for deeper insights into large language models

Reference 45

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This paper cites Linear convergence in federated learning: Tackling client heterogeneity and sparse gradients.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Linear convergence in federated learning: Tackling client heterogeneity and sparse gradients

Reference 46

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Observation 98f01d81-f0a8-4848-9fc5-9848a5bc71a3 · outbound

This paper cites Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Reference 47

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This paper cites Federated learning for smart healthcare: A survey.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning for smart healthcare: A survey

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:33.839823Z

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Observation 50b76e04-cea2-46d9-8e2f-d289f803a849 · outbound

This paper cites Fantastic weights and how to find them: Where to prune in dynamic sparse training.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fantastic weights and how to find them: Where to prune in dynamic sparse training

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:33.692341Z

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Observation 170bf5f2-bbf7-491d-871f-27f4fe7e87e7 · outbound

This paper cites The future of digital health with federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity The future of digital health with federated learning

Reference 50

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This paper cites Privacy-first health research with federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Privacy-first health research with federated learning

Reference 51

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Observation f901724d-4b21-4520-9fc8-df5c7ad158ba · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Very deep convolutional networks for large-scale image recognition

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:33.390586Z

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Observation 8afc7de2-7fb6-4001-9897-d1a1da6d9ef9 · outbound

This paper cites Federated reconstruction: Partially local federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated reconstruction: Partially local federated learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:33.302530Z

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Observation 45075c7c-0ee8-4568-8dad-54c7f18c95e1 · outbound

This paper cites Federated multi-task learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated multi-task learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:33.108719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4201c5af-f70c-47e4-a2a1-8091817a4b87 · outbound

This paper cites Fedselect: Personalized federated learning with customized selection of parameters for fine-tuning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedselect: Personalized federated learning with customized selection of parameters for fine-tuning

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.970855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 394183c3-786c-4669-9605-db470dc6542c · outbound

This paper cites Towards personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Towards personalized federated learning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.799625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a5f29e82-fe72-42c8-adef-04610337855f · outbound

This paper cites Fedgen: Generalizable federated learning for sequential data.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedgen: Generalizable federated learning for sequential data

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.624482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4fa4556a-c74c-4cc0-ac11-22a03d7698e1 · outbound

This paper cites Gradient sparsification for communication-efficient distributed optimization.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Gradient sparsification for communication-efficient distributed optimization

Reference 58

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Source-reported events for the cited work

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Observation 2c357a6b-4072-4ea0-89d1-f6d89a6c7020 · outbound

This paper cites Federated dropout—a simple approach for enabling federated learning on resource constrained devices.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated dropout—a simple approach for enabling federated learning on resource constrained devices

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.494715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 26f51148-c2e0-4952-a118-c1866d78383b · outbound

This paper cites A survey on federated learning: challenges and applications.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity A survey on federated learning: challenges and applications

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.356201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2db56f38-236d-4217-a9e6-dfc95ee7d3ce · outbound

This paper cites Dynamic sparse training versus dense training: The unexpected winner in image corruption robustness.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dynamic sparse training versus dense training: The unexpected winner in image corruption robustness

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.212231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0d39e952-8c6d-4b5d-9b27-bf5df01a8f5c · outbound

This paper cites Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:32.046871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ebaf4a79-ae09-423a-97a5-7606e617f3d5 · outbound

This paper cites Dynamic sparse network for time series classification: Learning what to see.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dynamic sparse network for time series classification: Learning what to see

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:31.922998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 04477e81-fd87-403c-8547-bbe2fd59fd40 · outbound

This paper cites Federated machine learning: Concept and applications.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated machine learning: Concept and applications

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:31.690177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08924eeb-62a6-4f1d-8347-ec47fef78bb9 · outbound

This paper cites Fedmix: Approximation of mixup under mean augmented federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedmix: Approximation of mixup under mean augmented federated learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:31.440431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d9998c98-518e-46c7-8ff2-483d3d69d3f2 · outbound

This paper cites Salvaging Federated Learning by Local Adaptation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Salvaging Federated Learning by Local Adaptation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:30.082217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9d74c3b-0664-4d26-a7c5-300c1a912aec · outbound

This paper cites What do we mean by generalization in federated learning? In International Conference on Learning Representations, 2022.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity What do we mean by generalization in federated learning? In International Conference on Learning Representations, 2022

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:31.325541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation add2da19-5ed6-46a5-8496-33ec7c0d7025 · outbound

This paper cites Fedala: Adaptive local aggregation for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedala: Adaptive local aggregation for personalized federated learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:31.071637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5077a07a-0e6f-4e73-97c7-c00ba6c20595 · outbound

This paper cites Parameterized knowledge transfer for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Parameterized knowledge transfer for personalized federated learning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:30.861352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 07221ebc-8494-4dad-a89d-46d3e020f806 · outbound

This paper cites Federated Learning with Non-IID Data.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Learning with Non-IID Data

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:30.460023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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