FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning | Paper Citation Record

Observation 348309c4-d84f-4f85-aeba-ddb4f3d0c17c · outbound

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

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 1

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Observation 7bb0f028-a460-41dd-99b0-8836a1e52ee7 · outbound

This paper cites Federated Learning: Challenges, Methods, and Future Directions.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Learning: Challenges, Methods, and Future Directions

Reference 2

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Observation 87a77ba7-f290-4b4c-ae4a-957331ef8db1 · outbound

This paper cites Challenges, Applications and Design Aspects of Federated Learning: A Survey.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Challenges, Applications and Design Aspects of Federated Learning: A Survey

Reference 3

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This paper cites Self-Sovereign Identity Management for Hierarchical Federated Learning in Vehicular Networks.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Self-Sovereign Identity Management for Hierarchical Federated Learning in Vehicular Networks

Reference 4

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This paper cites Local Model Poisoning Attacks to Byzantine-Robust Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

Reference 5

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This paper cites Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning

Reference 6

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Observation 078abc9a-c1a3-4c13-ace5-2d5156e31530 · outbound

This paper cites How To Backdoor Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning How To Backdoor Federated Learning

Reference 7

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Observation 695c24ea-3ca5-4e52-8e93-e725619d5e5c · outbound

This paper cites Free-riders in Federated Learning: Attacks and Defenses.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Free-riders in Federated Learning: Attacks and Defenses

Reference 8

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Observation 1e99aeb7-d1a1-499a-bdec-4037552df6d0 · outbound

This paper cites Blockchain for Federated Learning Toward Secure Distributed Machine Learning Systems: A Systemic Survey.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Blockchain for Federated Learning Toward Secure Distributed Machine Learning Systems: A Systemic Survey

Reference 9

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This paper cites A Blockchain-based Trust System for Decentralised Applications: When trustless needs trust.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning A Blockchain-based Trust System for Decentralised Applications: When trustless needs trust

Reference 10

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Observation f25630a6-92ae-41e8-99be-7f6a3391ce84 · outbound

This paper cites Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification

Reference 11

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Observation d80d2828-67eb-46ef-9aae-7da563bbde04 · outbound

This paper cites Biscotti: A Blockchain System for Private and Secure Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Biscotti: A Blockchain System for Private and Secure Federated Learning

Reference 12

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This paper cites Proof-of-Reputation: An Alternative Consensus Mechanism for Blockchain Systems.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Proof-of-Reputation: An Alternative Consensus Mechanism for Blockchain Systems

Reference 13

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This paper cites MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics

Reference 14

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Observation 007d08e2-7728-45c0-9132-f17943dc2c2e · outbound

This paper cites Efficiency in Digital Economies -- A Primer on Tokenomics.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Efficiency in Digital Economies -- A Primer on Tokenomics

Reference 15

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Observation b6ef2da9-9c38-41e2-857d-a98d5a18f99d · outbound

This paper cites Engineering Token Economy with System Modeling.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Engineering Token Economy with System Modeling

Reference 16

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Observation 3298b7bc-0616-454c-9673-856395f770cc · outbound

This paper cites Computational Attestations of Polynomial Integrity Towards Verifiable Machine Learning; 2024.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Computational Attestations of Polynomial Integrity Towards Verifiable Machine Learning; 2024

Reference 17

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This paper cites ZHE: Efficient Zero-Knowledge Proofs for HE Evaluations; 2025.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning ZHE: Efficient Zero-Knowledge Proofs for HE Evaluations; 2025

Reference 18

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Observation 71b464fe-e46d-4122-b905-45033b7bfb07 · outbound

This paper cites Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent

Reference 19

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This paper cites Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning

Reference 20

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This paper cites Developing Hessian–Free Second–Order Adversarial Examples for Adversarial Training.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Developing Hessian–Free Second–Order Adversarial Examples for Adversarial Training

Reference 21

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Observation 3393e94e-163e-4b98-b09b-d1de8f448765 · outbound

This paper cites Federated Learning: Overview, strategies, applications, tools and future directions.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Learning: Overview, strategies, applications, tools and future directions

Reference 22

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Observation 41f2dbaa-c02d-49be-b8c9-dc5a2ec5cfbd · outbound

This paper cites Federated Learning: A Distributed Shared Machine Learning Method.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Learning: A Distributed Shared Machine Learning Method

Reference 23

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Observation 7d4bb1dd-1469-45c1-afd4-9029a15f8fb5 · outbound

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

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 24

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This paper cites Federated Averaging: The Backbone of Federated Learning; 2024.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Averaging: The Backbone of Federated Learning; 2024

Reference 25

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This paper cites Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey

Reference 26

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This paper cites Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective

Reference 27

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This paper cites Communication-Efficient Federated Learning for Resource-Constrained Edge Devices.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Communication-Efficient Federated Learning for Resource-Constrained Edge Devices

Reference 28

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This paper cites Federated Learning with Non-IID Data.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Federated Learning with Non-IID Data

Reference 29

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Observation e96bc13d-95b7-4f54-9b66-5a774bb3a05c · outbound

This paper cites A Survey on Heterogeneous Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning A Survey on Heterogeneous Federated Learning

Reference 30

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Observation a0be0c50-c864-43c0-9377-b205fa4653a3 · outbound

This paper cites Heterogeneous Federated Learning: State-of-the-art and Research Challenges.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Heterogeneous Federated Learning: State-of-the-art and Research Challenges

Reference 31

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Observation 40b0017f-dfec-4c41-adcc-e928ef7c4595 · outbound

This paper cites The Limitations of Federated Learning in Sybil Settings.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning The Limitations of Federated Learning in Sybil Settings

Reference 32

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This paper cites DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences

Reference 33

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This paper cites Securing Federated Learning Against Overwhelming Collusive Attackers.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Securing Federated Learning Against Overwhelming Collusive Attackers

Reference 34

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Observation 28180337-e497-41ae-b02b-fc7b2a9f79d6 · outbound

This paper cites Deep Leakage from Gradients.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Deep Leakage from Gradients

Reference 35

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This paper cites A Survey of Distributed Consensus Protocols for Blockchain Networks.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning A Survey of Distributed Consensus Protocols for Blockchain Networks

Reference 36

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This paper cites Consensus Algorithms of Distributed Ledger Technology -- A Comprehensive Analysis.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Consensus Algorithms of Distributed Ledger Technology -- A Comprehensive Analysis

Reference 37

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Observation c5cc3d96-2a8a-421b-b234-3e4d37dc386b · outbound

This paper cites The Byzantine Generals Problem.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning The Byzantine Generals Problem

Reference 38

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Observation 466d9e5a-2fd5-4ef5-96ee-1e15161d5629 · outbound

This paper cites Practical Byzantine Fault Tolerance.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Practical Byzantine Fault Tolerance

Reference 39

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Observation 434edf1c-a6ac-4a41-8e8e-ac3a54aefd5b · outbound

This paper cites HotStuff: BFT Consensus with Linearity and Responsiveness.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning HotStuff: BFT Consensus with Linearity and Responsiveness

Reference 40

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Observation a8169d9c-b433-45b7-8914-6fb7be98ce50 · outbound

This paper cites Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey

Reference 41

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This paper cites Beyond the Tragedy of the Commons: Building A Reputation System for Generative Multi-agent Systems.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Beyond the Tragedy of the Commons: Building A Reputation System for Generative Multi-agent Systems

Reference 42

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This paper cites DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:53.638866Z

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Observation 0549bd07-0fdb-4352-8c91-93396c722630 · outbound

This paper cites Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:53.475170Z

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Observation 709f238c-18fa-4f52-92ae-0967a0989b2b · outbound

This paper cites In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems

Reference 45

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Observation bddf2f22-cd64-43d4-b9a3-85329c58870d · outbound

This paper cites Using Game Theory to Design Resilient Token Economies; 2024.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Using Game Theory to Design Resilient Token Economies; 2024

Reference 46

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This paper cites Applying Game Theory in Token Design; 2024.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Applying Game Theory in Token Design; 2024

Reference 47

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Observation dd61bb98-9c89-410f-a159-8a85d29430ee · outbound

This paper cites Tokenomics and Game Theory: Understanding the Economic Incentives of Blockchain Networks; 2024.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Tokenomics and Game Theory: Understanding the Economic Incentives of Blockchain Networks; 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:52.759064Z

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Observation f8e1668e-99cc-4e39-a900-cbb168c6fec7 · outbound

This paper cites Game Theory and Blockchain; 2025.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Game Theory and Blockchain; 2025

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:52.603349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 054b9732-e819-4100-8302-6d389371196c · outbound

This paper cites Incentive Compatibility in Consensus Protocols and DAOs: A Game-Theoretic Approach.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Incentive Compatibility in Consensus Protocols and DAOs: A Game-Theoretic Approach

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:52.468462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6cb8d9c4-a0d1-45cd-b1f2-d684219d5c8c · outbound

This paper cites Game Theory-Based Incentive Design in Blockchain Networks.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Game Theory-Based Incentive Design in Blockchain Networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:52.196475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 55b1aa78-c1bf-4817-9c22-4383c9b7b9da · outbound

This paper cites A Survey on Homomorphic Encryption Schemes: Theory and Implementation.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning A Survey on Homomorphic Encryption Schemes: Theory and Implementation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:52.088049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fbf31244-2b14-48ef-9d5c-dc7f240a6b29 · outbound

This paper cites PBFL: A Privacy-Preserving Blockchain-Based Federated Learning Framework With Homomorphic Encryption and Single Masking.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning PBFL: A Privacy-Preserving Blockchain-Based Federated Learning Framework With Homomorphic Encryption and Single Masking

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.968899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9d9da573-d4ff-4997-878c-273974100ccb · outbound

This paper cites A Review of Homomorphic Encryption for Privacy-Preserving Computations.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning A Review of Homomorphic Encryption for Privacy-Preserving Computations

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.797384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d2c326c9-0574-44bb-a732-aec04dda2ebb · outbound

This paper cites Advancing Blockchain-based Federated Learning through Verifiable Off-chain Computations.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Advancing Blockchain-based Federated Learning through Verifiable Off-chain Computations

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.623536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5c1ba5c9-cd6d-4690-93a2-046f003e2d02 · outbound

This paper cites Mathematical Proposal for Securing Split Learning Using Homomorphic Encryption and Zero-Knowledge Proofs.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Mathematical Proposal for Securing Split Learning Using Homomorphic Encryption and Zero-Knowledge Proofs

Reference 56

Resolution: verified exact; doi, observed 2026-08-06T16:11:48.034339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9ddfcea7-2ab3-48fa-80b7-931094df3466 · outbound

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

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.452874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9283a5e-eab2-4ec5-9fe7-1a796fb40a87 · outbound

This paper cites Robust Federated Learning: Maximum Correntropy Aggregation Against Byzantine Attacks.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Robust Federated Learning: Maximum Correntropy Aggregation Against Byzantine Attacks

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.278100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5f58fbe-14f9-4722-8c3b-457d02883016 · outbound

This paper cites An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:51.112935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 960bf4db-c8fb-48d9-94f7-81c86a391f6f · outbound

This paper cites Adapting Aggregation Rule for Robust Federated Learning under Dynamic Attacks.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Adapting Aggregation Rule for Robust Federated Learning under Dynamic Attacks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:50.916666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fe5b4ea0-7993-4461-b76b-e19ab18df897 · outbound

This paper cites MAB-RFL: A multi-armed bandit based robust federated learning framework.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning MAB-RFL: A multi-armed bandit based robust federated learning framework

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:50.714103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 57c46f67-549f-4f4c-b18d-f78436dc6dd6 · outbound

This paper cites UCB-CS: A New Bandit-Based Approach for Communication-Efficient Client Selection in Federated Learning.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning UCB-CS: A New Bandit-Based Approach for Communication-Efficient Client Selection in Federated Learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:50.535369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ea08f3b2-1711-4c74-ad3c-d275f2e25151 · outbound

This paper cites FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:11:48.660399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cb214c2f-d1ca-435b-bdee-0092485d0338 · outbound

This paper cites Fedstrategist; 2025.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Fedstrategist; 2025

Reference 64

Resolution: verified exact; doi, observed 2026-08-06T16:11:47.739360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9acb9fb6-b8e8-4ec5-940d-6fc6c923b0d6 · outbound

This paper cites Free-riders in Federated Learning: Attacks and Defenses.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Free-riders in Federated Learning: Attacks and Defenses

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T16:11:41.340457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e8ac757-38e6-4329-a909-4222677b27c8 · outbound

This paper cites Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:11:48.967521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 29663b2e-aafc-4052-8511-91cd852223f2 · outbound

This paper cites An A{\alpha}-spectral radius for the existence of {P3, P4, P5}-factors in graphs.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning An A{\alpha}-spectral radius for the existence of {P3, P4, P5}-factors in graphs

Reference 2025

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:11:49.210511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d8cf92e-ce21-431f-bd50-22671651e74f · outbound

This paper cites an unresolved cited work.

FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning Unresolved cited work

Reference 3791

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:11:52.313998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers