FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense | Paper Citation Record

Observation 584d4c04-5761-4676-9a56-201c843ba053 · outbound

This paper cites Dynamic multi-interest graph neural network for session-based recommendation.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Dynamic multi-interest graph neural network for session-based recommendation

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Observation eddc17c7-514d-4ea6-9c3f-04757b7f6301 · outbound

This paper cites Dual graph neural networks for dynamic users’ behavior prediction on social networking services.IEEE Transactions on Computational Social Systems, 11(5):7020–7031, 2024.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Dual graph neural networks for dynamic users’ behavior prediction on social networking services.IEEE Transactions on Computational Social Systems, 11(5):7020–7031, 2024

Reference 2

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Observation f1863bcc-ccf6-4e93-8271-f7b5b6b3ed49 · outbound

This paper cites Refine then classify: Robust graph neural networks with reliable neighborhood contrastive refinement.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Refine then classify: Robust graph neural networks with reliable neighborhood contrastive refinement

Reference 3

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Observation b59ed9ab-6551-43cb-98d9-7f4be1dfb7ed · outbound

This paper cites Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network

Reference 4

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Observation 15ca1e49-336b-4509-b223-51c46c69f25c · outbound

This paper cites More is better (mostly): On the backdoor attacks in federated graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense More is better (mostly): On the backdoor attacks in federated graph neural networks

Reference 5

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Observation 1bc146c2-2aed-4817-83b9-b36879ef84fe · outbound

This paper cites Backdoor attacks to graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Backdoor attacks to graph neural networks

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Observation 9a628f9f-8f7c-47a2-9851-d2c4c749b931 · outbound

This paper cites Unnoticeable backdoor attacks on graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unnoticeable backdoor attacks on graph neural networks

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Observation 9e60607b-5559-4052-a150-5d51f8635625 · outbound

This paper cites Rethinking graph backdoor attacks: A distribution- preserving perspective.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Rethinking graph backdoor attacks: A distribution- preserving perspective

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Observation a58788f3-d848-4162-a490-246385d5d999 · outbound

This paper cites Flmaacbd: Defending against backdoors in federated learning via model anomalous activation behavior detection.Knowledge-Based Systems, 289:111511, 2024.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Flmaacbd: Defending against backdoors in federated learning via model anomalous activation behavior detection.Knowledge-Based Systems, 289:111511, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T12:07:43.201107Z

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Observation 4e778912-27a6-4f3c-9696-7c79d4df3764 · outbound

This paper cites Pham, Khoa D.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Pham, Khoa D

Reference 10

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Observation 34bfd749-3e54-45a5-86f3-1a0ad014a8a9 · outbound

This paper cites Neurotoxin: Durable backdoors in federated learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Neurotoxin: Durable backdoors in federated learning

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Observation 2ecc43ca-eece-4610-b436-e851bca045bb · outbound

This paper cites A simple and yet fairly effective defense for graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense A simple and yet fairly effective defense for graph neural networks

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Resolution: unresolved; no resolver link, observed 2026-08-01T12:07:43.535716Z

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Observation efaba89e-9bbb-49f3-b1e9-d127d9b2e019 · outbound

This paper cites Robustness inspired graph backdoor defense.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Robustness inspired graph backdoor defense

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Observation 7d761871-e9ef-4ee6-af42-4c823dc9e5c3 · outbound

This paper cites Beyond redundancy: Information-aware unsupervised multiplex graph structure learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Beyond redundancy: Information-aware unsupervised multiplex graph structure learning

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Observation 87e59339-7e92-466e-99c8-b8be3dda45e0 · outbound

This paper cites Defending against backdoors in federated learning with robust learning rate.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Defending against backdoors in federated learning with robust learning rate

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Observation c82e5a6e-4cab-4587-8b88-d1769bafe4de · outbound

This paper cites Energy-based back- door defense against federated graph learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Energy-based back- door defense against federated graph learning

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Observation d5345c98-6734-49f4-b29f-2f79fbdbaa1a · outbound

This paper cites Data-centric Federated Graph Learning with Large Language Models.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Data-centric Federated Graph Learning with Large Language Models

Reference 17

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Observation bcfbf107-ad45-4130-acb4-236a9776a2e5 · outbound

This paper cites Llm-guided dynamic-umap for personalized federated graph learning.arXiv preprint arXiv:2511.09438, 2025.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Llm-guided dynamic-umap for personalized federated graph learning.arXiv preprint arXiv:2511.09438, 2025

Reference 18

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Observation af1b5c7c-4115-45bc-9ebe-5bf1174286da · outbound

This paper cites pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

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Observation 72cd2957-dfc3-4a2d-86a8-5c0b78e4eeb2 · outbound

This paper cites Personalized federated fine-tuning for llms via data-driven heterogeneous model architectures.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Personalized federated fine-tuning for llms via data-driven heterogeneous model architectures

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Observation 27085ec8-e83c-4cde-b78d-53fdade213cc · outbound

This paper cites Fedex-lora: Exact aggregation for federated and efficient fine-tuning of large language models.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Fedex-lora: Exact aggregation for federated and efficient fine-tuning of large language models

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Observation 2ea82013-208c-43e9-9fd4-63594a56a1c7 · outbound

This paper cites Fedalt: Federated fine-tuning through adaptive local training with rest-of-world lora.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Fedalt: Federated fine-tuning through adaptive local training with rest-of-world lora

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Observation be0043f7-bc6f-492e-ae8c-3fd28c729e16 · outbound

This paper cites Federatedscope- gnn: Towards a unified, comprehensive and efficient package for federated graph learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Federatedscope- gnn: Towards a unified, comprehensive and efficient package for federated graph learning

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Observation 644a5805-0261-43e1-9d18-790ff0d8edbc · outbound

This paper cites E-sage: Explainability- based defense against backdoor attacks on graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense E-sage: Explainability- based defense against backdoor attacks on graph neural networks

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Observation e84b4d3a-7ac7-4b8c-8050-46413e374e67 · outbound

This paper cites Dshield: Defending against backdoor attacks on graph neural networks via discrepancy learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Dshield: Defending against backdoor attacks on graph neural networks via discrepancy learning

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Observation f1133080-d14a-4eb4-8d19-05ae698189cc · outbound

This paper cites Gnnguard: Defending graph neural networks against adversarial attacks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Gnnguard: Defending graph neural networks against adversarial attacks

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Observation 4fad02d0-0ee5-45bc-bfaf-9f9f67070a1d · outbound

This paper cites Graph attention networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Graph attention networks

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Observation c9b5b2f2-da73-4fe7-9a6b-3220412c5937 · outbound

This paper cites Comprehensive risk assessment method of power grid based on grey relational weight game theory.IOP Conference Series: Earth and Environmental Science, 453(1):12068, 2020.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Comprehensive risk assessment method of power grid based on grey relational weight game theory.IOP Conference Series: Earth and Environmental Science, 453(1):12068, 2020

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Observation ef32ad0c-921b-47db-abcb-2ef1a0d7e6e1 · outbound

This paper cites Evidential supplier selection based on DEMATEL and game theory.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Evidential supplier selection based on DEMATEL and game theory

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Observation 07ac184d-9d32-41eb-ad1f-f12a56f5e918 · outbound

This paper cites Collective classification in network data.AI Magazine, 29(3):93–106, 2008.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Collective classification in network data.AI Magazine, 29(3):93–106, 2008

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Observation 9840e1a9-d196-4b64-a3c9-d4053f86e93a · outbound

This paper cites Graphsaint: Graph sampling based inductive learning method.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Graphsaint: Graph sampling based inductive learning method

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This paper cites Open graph benchmark: Datasets for machine learning on graphs.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Open graph benchmark: Datasets for machine learning on graphs

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This paper cites The Llama 3 Herd of Models.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense The Llama 3 Herd of Models

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This paper cites Garnet: Reduced-rank topology learning for robust and scalable graph neural networks.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Garnet: Reduced-rank topology learning for robust and scalable graph neural networks

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Observation 9ee40238-d5ce-4e72-8127-3d9fa13b0152 · outbound

This paper cites Adversarial attacks on graph neural networks via meta learning.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Adversarial attacks on graph neural networks via meta learning

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This paper cites Relative to the base GAT, the additional structural operation is the similarity-aware edge scoring in Eq.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Relative to the base GAT, the additional structural operation is the similarity-aware edge scoring in Eq

Reference 36

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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This paper cites From Eqs.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense From Eqs

Reference 38

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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This paper cites Instead, the server keeps the remaining L−k semantic blocks and provides detached teacher targets for distillation.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Instead, the server keeps the remaining L−k semantic blocks and provides detached teacher targets for distillation

Reference 41

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This paper cites FedLoRA+GAT + one server-side LLM teacher,.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense FedLoRA+GAT + one server-side LLM teacher,

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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Observation 42bd970b-246c-47a0-9210-d78cef9d55ee · outbound

This paper cites In FL scenarios, the attack surface becomes even broader.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense In FL scenarios, the attack surface becomes even broader

Reference 45

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This paper cites They establish a comprehensive benchmark that systematically evaluates backdoor attacks in federated graph learning, facilitating more standardized comparisons across methods.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense They establish a comprehensive benchmark that systematically evaluates backdoor attacks in federated graph learning, facilitating more standardized comparisons across methods

Reference 46

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense Unresolved cited work

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This paper cites 19 Running Title for Header A.6 Parameter Settings We summarize the parameter settings used for Citeseer, Pubmed, Flickr, and Ogb-arxiv according to the released implementation.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense 19 Running Title for Header A.6 Parameter Settings We summarize the parameter settings used for Citeseer, Pubmed, Flickr, and Ogb-arxiv according to the released implementation

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