Chulin Xie

Orcid: 0000-0002-5460-3785

According to our database¹, Chulin Xie authored at least 35 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

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On csauthors.net:

Bibliography

2024

LLM-PBE: Assessing Data Privacy in Large Language Models.

[BibT_eX]

[DOI]

Proc. VLDB Endow., July, 2024

On Memorization of Large Language Models in Logical Reasoning.

[BibT_eX]

[DOI]

CoRR, 2024

Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Optimization.

[BibT_eX]

[DOI]

CoRR, 2024

Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning.

[BibT_eX]

[DOI]

CoRR, 2024

Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs.

[BibT_eX]

[DOI]

CoRR, 2024

TablePuppet: A Generic Framework for Relational Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs.

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Differentially Private Synthetic Data via Foundation Model APIs 2: Text.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Effective and Efficient Federated Tree Learning on Hybrid Data.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Perada: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?

[BibT_eX]

[DOI]

CoRR, 2023

FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs.

[BibT_eX]

[DOI]

CoRR, 2023

PerAda: Parameter-Efficient and Generalizable Federated Learning Personalization with Guarantees.

[BibT_eX]

[DOI]

CoRR, 2023

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

Uncovering the Connection Between Differential Privacy and Certified Robustness of Federated Learning against Poisoning Attacks.

[BibT_eX]

[DOI]

CoRR, 2022

Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions.

[BibT_eX]

[DOI]

CoRR, 2022

UniFed: A Benchmark for Federated Learning Frameworks.

[BibT_eX]

[DOI]

CoRR, 2022

FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data.

[BibT_eX]

[DOI]

CoRR, 2022

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM.

[BibT_eX]

[DOI]

CoRR, 2022

CoPur: Certifiably Robust Collaborative Inference via Feature Purification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting.

[BibT_eX]

[DOI]

CoRR, 2021

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Style-Based Point Generator With Adversarial Rendering for Point Cloud Completion.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

DBA: Distributed Backdoor Attacks against Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Attack-Resistant Federated Learning with Residual-based Reweighting.

[BibT_eX]

[DOI]

CoRR, 2019

Zhejiang University at ImageCLEF 2019 Visual Question Answering in the Medical Domain.

[BibT_eX]

[DOI]

Proceedings of the Working Notes of CLEF 2019, 2019

2018

Data Quality Transaction on Different Distributed Ledger Technologies.

[BibT_eX]

[DOI]

Proceedings of the Big Scientific Data Management, 2018

Chulin Xie

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