DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation | Paper Citation Record

Observation c1f3cca0-df82-4612-9c7a-627296a61ec3 · outbound

This paper cites Resolution on generative artificial intelligence systems,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Resolution on generative artificial intelligence systems,

Reference 1

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Observation feba1996-7d03-4cfc-8daf-488f4745a411 · outbound

This paper cites Domain adaptation: Challenges, methods, datasets, and applications,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Domain adaptation: Challenges, methods, datasets, and applications,

Reference 2

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Observation e5d63847-7aa8-4396-9230-b2dd9ebafebf · outbound

This paper cites The challenges of data quality and data quality assessment in the big data era,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation The challenges of data quality and data quality assessment in the big data era,

Reference 3

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Observation 772b2ffd-95ec-48cb-8321-f6666abd61f4 · outbound

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

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 4

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Observation 155b501c-4a7a-44ce-9aa3-c87fe7ca0560 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated Learning: Strategies for Improving Communication Efficiency

Reference 5

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This paper cites A review on traditional machine learning and deep learning models for wbcs classification in blood smear images,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A review on traditional machine learning and deep learning models for wbcs classification in blood smear images,

Reference 6

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Observation b5f5e30e-de6f-4865-afa0-514458971511 · outbound

This paper cites Federated vs. centralized machine learning under privacy-elastic users: A comparative analysis,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated vs. centralized machine learning under privacy-elastic users: A comparative analysis,

Reference 7

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Observation c1e1db95-8872-4dd0-bb42-6b927cce3a85 · outbound

This paper cites A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.428642Z

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Observation cf95aafb-33ec-4fe5-9eca-7b25380536c2 · outbound

This paper cites Federated benchmarking of medical artificial intelligence with medperf,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated benchmarking of medical artificial intelligence with medperf,

Reference 9

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Observation 14e9129c-d3df-46cb-afc8-fa3656457580 · outbound

This paper cites Feder- ated learning in autonomous vehicles using cross- border training,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Feder- ated learning in autonomous vehicles using cross- border training,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.415483Z

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Observation f38a0d9c-5d08-4526-aa48-92e60d9ef545 · outbound

This paper cites Securing secure aggregation: mitigating multi-round privacy leakage in federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Securing secure aggregation: mitigating multi-round privacy leakage in federated learning,

Reference 11

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Observation e30e99f0-46e1-4ef5-acb8-1278c525ba99 · outbound

This paper cites Exploiting Unintended Feature Leakage in Collaborative Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Exploiting Unintended Feature Leakage in Collaborative Learning

Reference 12

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Observation 23c01f31-b798-4cb7-9aef-f33d58b5f7d8 · outbound

This paper cites A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions,

Reference 13

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Observation 9868d32a-2f64-4d47-9138-2d9f5200cb0b · outbound

This paper cites How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?

Reference 14

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Observation 524b6a61-ed4b-44db-8cc4-20dd8003ad39 · outbound

This paper cites Federated learning minimal model replacement attack using optimal transport: An attacker perspective,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated learning minimal model replacement attack using optimal transport: An attacker perspective,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.368165Z

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Observation 6e4ad31a-d509-4e3d-be19-301bef8d193c · outbound

This paper cites How To Backdoor Federated Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation How To Backdoor Federated Learning

Reference 16

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Observation a062cad9-8b5c-41ed-8aac-8cdeaa316778 · outbound

This paper cites Analyzing federated learning through an adversarial lens,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Analyzing federated learning through an adversarial lens,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.347045Z

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Observation 0c6891a6-672b-4fb5-a7b6-6ca8c5ad2b27 · outbound

This paper cites Dual Model Replacement:invisible Multi-target Backdoor Attack based on Federal Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Dual Model Replacement:invisible Multi-target Backdoor Attack based on Federal Learning

Reference 18

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Observation 6e2fabbe-7a43-421f-ac62-793dc3098327 · outbound

This paper cites Dba: Distributed backdoor attacks against federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Dba: Distributed backdoor attacks against federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.331456Z

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Observation b80eac43-57a8-48bf-87a0-9ce30ef92c5f · outbound

This paper cites Local model poisoning attacks to Byzantine-Robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Local model poisoning attacks to Byzantine-Robust federated learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.316466Z

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Observation a178e583-73fd-4f2c-b21b-11620640a8b9 · outbound

This paper cites A gan- based data poisoning attack against federated learning systems and its countermeasure,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A gan- based data poisoning attack against federated learning systems and its countermeasure,

Reference 21

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Observation edb434fb-bb20-4dfe-884a-54b3812c3449 · outbound

This paper cites Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-15T16:13:03.854923Z

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Observation 05e0b10d-586c-4145-bdc1-6d2a6c7ad8be · outbound

This paper cites Exploiting defenses against gan-based feature inference attacks in federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Exploiting defenses against gan-based feature inference attacks in federated learning,

Reference 23

Resolution: verified exact; doi, observed 2026-08-15T16:13:03.452949Z

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Observation 8c911b94-3d48-456d-b734-e0e87d18057b · outbound

This paper cites Localmodelpoisoning attacks to byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Localmodelpoisoning attacks to byzantine-robust federated learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.289085Z

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Observation 0f26761b-6917-4cce-a586-26f48c4123e8 · outbound

This paper cites Data Poisoning Attacks Against Federated Learning Systems.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Data Poisoning Attacks Against Federated Learning Systems

Reference 25

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Observation 224c9607-ea27-4cf2-ae66-ae474b48c14c · outbound

This paper cites Manipulating machine learning: Poisoning attacks and countermeasures for regression learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Manipulating machine learning: Poisoning attacks and countermeasures for regression learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.273808Z

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Observation 1ceef9b5-31d5-407c-ae7f-496cca465903 · outbound

This paper cites Machine learning with adversaries: Byzantine tolerant gradient descent,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Machine learning with adversaries: Byzantine tolerant gradient descent,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.256030Z

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Observation fdf4ec20-a2c2-4578-aafa-3d7118c6a711 · outbound

This paper cites The hidden vulnerability of distributed learning in byzantium,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation The hidden vulnerability of distributed learning in byzantium,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.241075Z

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Observation 28ec73ce-7cbf-4e5e-ac02-23025f785766 · outbound

This paper cites Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Reference 30

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Observation d9e1742c-b303-449a-b65d-15bcbef005e2 · outbound

This paper cites Practical secure aggregation for privacy-preserving machine learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Practical secure aggregation for privacy-preserving machine learning,

Reference 31

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Observation c6cf9ca1-accf-4ba0-b7d5-52c50c04300c · outbound

This paper cites Privacy-preserving deep learning via additively homomorphic encryption,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy-preserving deep learning via additively homomorphic encryption,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.242697Z

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Observation 3a10635c-11a2-4d52-8585-a6ecf5fd07d5 · outbound

This paper cites Homomorphic encryption for arithmetic of approximate numbers,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Homomorphic encryption for arithmetic of approximate numbers,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.248119Z

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Observation 0c2bbe87-d381-45b3-a8ae-44a0178c7d8a · outbound

This paper cites Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.216023Z

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Observation 14ca0219-e515-4c31-bbea-149e1e0c404a · outbound

This paper cites Lsfl: A lightweight and secure federated learning scheme for edge computing,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Lsfl: A lightweight and secure federated learning scheme for edge computing,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.202108Z

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Observation 9b4122ee-e596-4ef5-9d56-f6f6ff072238 · outbound

This paper cites FLOD: Oblivious defender for private byzantine-robust federated learning with dishonest-majority,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation FLOD: Oblivious defender for private byzantine-robust federated learning with dishonest-majority,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.188602Z

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Observation 1fb81c51-47de-4a06-854b-5ce9c2eb352f · outbound

This paper cites Differentially private byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Differentially private byzantine-robust federated learning,

Reference 37

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Observation be2ae0b7-464b-4e62-a931-492936dc95ed · outbound

This paper cites ELSA: secure aggregation for federated learning with malicious actors,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation ELSA: secure aggregation for federated learning with malicious actors,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.171284Z

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Observation 44596d24-6935-43be-8b63-7c71598fafc7 · outbound

This paper cites Byzantine-Tolerant Machine Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Tolerant Machine Learning

Reference 39

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Observation 79fe45ac-5e59-4031-801d-665f57eadc9e · outbound

This paper cites Batchcrypt: eﬀicient homomorphic encryption for cross-silo federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Batchcrypt: eﬀicient homomorphic encryption for cross-silo federated learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.155852Z

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Observation 582722e1-93f8-4c59-be3c-39ed52eddbe2 · outbound

This paper cites Verifynet: Secure and verifiable federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Verifynet: Secure and verifiable federated learning,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.138216Z

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Observation 8d382a30-9796-4d4f-84a5-1115e89c43ad · outbound

This paper cites Sear: Secure and eﬀicient aggregation for byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Sear: Secure and eﬀicient aggregation for byzantine-robust federated learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.119894Z

Source-reported events for the cited work

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Observation da3947c3-a54e-4fc1-b146-7f57a6e7e12d · outbound

This paper cites Pvd-fl: A privacy-preserving and verifiable decentralized federated learn- ing framework,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Pvd-fl: A privacy-preserving and verifiable decentralized federated learn- ing framework,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.102138Z

Source-reported events for the cited work

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Observation a17c0b48-59d7-49af-aee4-c564db33ae11 · outbound

This paper cites A Secure and Efficient Federated Learning Framework for NLP.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A Secure and Efficient Federated Learning Framework for NLP

Reference 44

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Source-reported events for the cited work

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Observation 78dd327e-c025-4abf-a2cb-cca5f6de353e · outbound

This paper cites Prio+: Privacy preserving aggregate statistics,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Prio+: Privacy preserving aggregate statistics,

Reference 45

Resolution: verified exact; doi, observed 2026-08-15T16:13:03.414483Z

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 91cebfd1-5696-44eb-967a-f30c40c5ed01 · outbound

This paper cites Secure Byzantine-Robust Machine Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Secure Byzantine-Robust Machine Learning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-15T16:13:03.612389Z

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 bef10875-d850-4915-8853-684541bd2afb · outbound

This paper cites Privacy- enhanced federated learning against poisoning adversaries,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy- enhanced federated learning against poisoning adversaries,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.086884Z

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 f4b1e374-886a-4d9e-8677-1b3c2a32bdf3 · outbound

This paper cites A differentially private federated learning model against poisoning attacks in edge computing,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A differentially private federated learning model against poisoning attacks in edge computing,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.072665Z

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 8d1a3cb4-b5dd-427b-b893-ead9ee84b133 · outbound

This paper cites Privacy-preserving and byzantine-robust federated learning,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Privacy-preserving and byzantine-robust federated learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.057223Z

Source-reported events for the cited work

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Observation 3eef01fa-94ad-4fb7-a755-96c1bfd5d4d5 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation FedMD: Heterogenous Federated Learning via Model Distillation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.332580Z

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Observation dd8d7893-4477-4785-a586-9600eb2cad1d · outbound

This paper cites Accurate diabetes risk stratification using machine learning: Role of missing value and outliers.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Accurate diabetes risk stratification using machine learning: Role of missing value and outliers

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.039924Z

Source-reported events for the cited work

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Observation 08b2d566-9178-478b-81f6-400021e60f0e · outbound

This paper cites Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.344172Z

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Observation e38a652a-f218-4b2c-8f77-237241a56772 · outbound

This paper cites Federated learning with differential privacy: Algorithms and performance analysis,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Federated learning with differential privacy: Algorithms and performance analysis,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.348973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 344b022f-9570-4ac2-a898-d7836829bd98 · outbound

This paper cites Local SGD converges fast and communicates little,.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Local SGD converges fast and communicates little,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.023373Z

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 31682073-9a24-4004-a907-1fdd268a1ba8 · outbound

This paper cites Available:https://www.usenix.org/conference/ usenixsecurity20/presentation/fang.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation Available:https://www.usenix.org/conference/ usenixsecurity20/presentation/fang

Reference 1622

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:13:04.301664Z

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 6e5910f5-0d55-4cbc-a759-57ec0d9ff0b7 · outbound

This paper cites SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:03.360478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers