Hui Liu

Orcid: 0000-0002-3555-3495

Affiliations:
  • Michigan State University, East Lansing, MI, USA


According to our database1, Hui Liu authored at least 44 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Rethinking Large Language Model Architectures for Sequential Recommendations.
CoRR, 2024

Mixture of Link Predictors.
CoRR, 2024

2023
Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles.
IEEE Trans. Knowl. Data Eng., December, 2023

Learning fair models without sensitive attributes: A generative approach.
Neurocomputing, December, 2023

Augment with Care: Enhancing Graph Contrastive Learning with Selective Spectrum Perturbation.
CoRR, 2023

Label-free Node Classification on Graphs with Large Language Models (LLMS).
CoRR, 2023

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models.
CoRR, 2023

On the Generalization of Training-based ChatGPT Detection Methods.
CoRR, 2023

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs.
CoRR, 2023

Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective.
CoRR, 2023

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models.
CoRR, 2023

Sharpness-Aware Data Poisoning Attack.
CoRR, 2023

Counterfactual Learning on Graphs: A Survey.
CoRR, 2023

Enhancing Graph Representations Learning with Decorrelated Propagation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Generative Diffusion Models on Graphs: Methods and Applications.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Probabilistic Categorical Adversarial Attack and Adversarial Training.
Proceedings of the International Conference on Machine Learning, 2023

Single-Cell Multimodal Prediction via Transformers.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Learning Representations for Hyper-Relational Knowledge Graphs.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.
CoRR, 2022

Rating Distribution Calibration for Selection Bias Mitigation in Recommendations.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Enhancing Individual Fairness through Propensity Score Matching.
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Toward Annotator Group Bias in Crowdsourcing.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Multi-Type Urban Crime Prediction.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
The Untold Secrets of WiFi-Calling Services: Vulnerabilities, Attacks, and Countermeasures.
IEEE Trans. Mob. Comput., 2021

UserSim: User Simulation via Supervised GenerativeAdversarial Network.
Proceedings of the WWW '21: The Web Conference 2021, 2021

AutoDim: Field-aware Embedding Dimension Searchin Recommender Systems.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

AutoLoss: Automated Loss Function Search in Recommendations.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations.
Proceedings of the IEEE International Conference on Data Mining, 2021

Attacking Black-box Recommendations via Copying Cross-domain User Profiles.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review.
Int. J. Autom. Comput., 2020

Memory-efficient Embedding for Recommendations.
CoRR, 2020

Learning from Incomplete Labeled Data via Adversarial Data Generation.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Sequence Learning with Side Dependencies.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Does Gender Matter? Towards Fairness in Dialogue Systems.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Whole-Chain Recommendations.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning Multi-Level Dependencies for Robust Word Recognition.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018
The Untold Secrets of Operational Wi-Fi Calling Services: Vulnerabilities, Attacks, and Countermeasures.
CoRR, 2018


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