Hui Liu

According to our database, Hui Liu authored at least 65 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Empowering Molecule Discovery for Molecule-Caption Translation With Large Language Models: A ChatGPT Perspective.

Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, Qing Li

IEEE Trans. Knowl. Data Eng., November, 2024

Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge.

Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang

CoRR, 2024

Exploring Social Desirability Response Bias in Large Language Models: Evidence from GPT-4 Simulations.

Sanguk Lee, Kaiqi Yang, Tai-Quan Peng, Ruth Heo, Hui Liu

CoRR, 2024

Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions.

Xianren Zhang, Xianfeng Tang, Hui Liu, Zongyu Wu, Qi He, Dongwon Lee, Suhang Wang

CoRR, 2024

Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study.

Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing

CoRR, 2024

A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization.

Yucheng Chu, Hang Li, Kaiqi Yang, Harry Shomer, Hui Liu, Yasemin Copur-Gencturk, Jiliang Tang

CoRR, 2024

A Survey of Mamba.

Haohao Qu, Liangbo Ning, Rui An, Wenqi Fan, Tyler Derr, Hui Liu, Xin Xu, Qing Li

CoRR, 2024

Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models.

Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 2024

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data.

Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang

CoRR, 2024

A Pure Transformer Pretraining Framework on Text-attributed Graphs.

Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu

CoRR, 2024

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights.

Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang

CoRR, 2024

Graph Machine Learning in the Era of Large Language Models (LLMs).

Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li

CoRR, 2024

Rethinking Large Language Model Architectures for Sequential Recommendations.

Hanbing Wang, Xiaorui Liu, Wenqi Fan, Xiangyu Zhao, Venkataramana Kini, Devendra Yadav, Fei Wang, Zhen Wen, Jiliang Tang, Hui Liu

CoRR, 2024

Mixture of Link Predictors.

Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang

CoRR, 2024

Copyright Protection in Generative AI: A Technical Perspective.

Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang

CoRR, 2024

Data Poisoning for In-context Learning.

Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang

CoRR, 2024

Neural Style Protection: Counteracting Unauthorized Neural Style Transfer.

Yaxin Li, Jie Ren, Han Xu, Hui Liu

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Sharpness-Aware Data Poisoning Attack.

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Structural Fairness-aware Active Learning for Graph Neural Networks.

Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Label-free Node Classification on Graphs with Large Language Models (LLMs).

Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Are Large Language Models (LLMs) Good Social Predictors?

Kaiqi Yang, Hang Li, Hongzhi Wen, Tai-Quan Peng, Jiliang Tang, Hui Liu

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

On the Generalization of Training-based ChatGPT Detection Methods.

Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang

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

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis.

Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Spectral-Aware Augmentation for Enhanced Graph Representation Learning.

Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Content Knowledge Identification with Multi-agent Large Language Models (LLMs).

Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu

Proceedings of the Artificial Intelligence in Education - 25th International Conference, 2024

2023

Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles.

Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang

IEEE Trans. Knowl. Data Eng., December, 2023

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

Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang

SIGKDD Explor., December, 2023

Learning fair models without sensitive attributes: A generative approach.

Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang

Neurocomputing, December, 2023

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

Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu

CoRR, 2023

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

Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang

CoRR, 2023

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

Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Jiliang Tang

CoRR, 2023

Sharpness-Aware Data Poisoning Attack.

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang

CoRR, 2023

Self-Explainable Graph Neural Networks for Link Prediction.

Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang

CoRR, 2023

Counterfactual Learning on Graphs: A Survey.

Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang

CoRR, 2023

Enhancing Graph Representations Learning with Decorrelated Propagation.

Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Generative Diffusion Models on Graphs: Methods and Applications.

Chengyi Liu, Wenqi Fan, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Probabilistic Categorical Adversarial Attack and Adversarial Training.

Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang

Proceedings of the International Conference on Machine Learning, 2023

Single-Cell Multimodal Prediction via Transformers.

Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data.

Wentao Wang, Harry Shomer, Yuxuan Wan, Yaxin Li, Jiangtao Huang, Hui Liu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Learning Representations for Hyper-Relational Knowledge Graphs.

Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu

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.

Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang

CoRR, 2022

Rating Distribution Calibration for Selection Bias Mitigation in Recommendations.

Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Hui Liu, Jiliang Tang, Youlong Cheng

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.

Enyan Dai, Wei Jin, Hui Liu, Suhang Wang

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.

Hamid Karimi, Muhammad Fawad Akbar Khan, Haochen Liu, Tyler Derr, Hui Liu

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations.

Pengfei He, Haochen Liu, Xiangyu Zhao, Hui Liu, Jiliang Tang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Toward Annotator Group Bias in Crowdsourcing.

Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Multi-Type Urban Crime Prediction.

Xiangyu Zhao, Wenqi Fan, Hui Liu, Jiliang Tang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

The Untold Secrets of WiFi-Calling Services: Vulnerabilities, Attacks, and Countermeasures.

Tian Xie, Guan-Hua Tu, Bangjie Yin, Chi-Yu Li, Chunyi Peng, Mi Zhang, Hui Liu, Xiaoming Liu

IEEE Trans. Mob. Comput., 2021

UserSim: User Simulation via Supervised GenerativeAdversarial Network.

Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang

Proceedings of the WWW '21: The Web Conference 2021, 2021

AutoDim: Field-aware Embedding Dimension Searchin Recommender Systems.

Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long

Proceedings of the WWW '21: The Web Conference 2021, 2021

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily.

Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

AutoLoss: Automated Loss Function Search in Recommendations.

Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang

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.

Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang

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.

Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, Xiwang Yang

Proceedings of the IEEE International Conference on Data Mining, 2021

Attacking Black-box Recommendations via Copying Cross-domain User Profiles.

Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems.

Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Jiliang Tang, Hui Liu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review.

Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain

Int. J. Autom. Comput., 2020

Memory-efficient Embedding for Recommendations.

Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long

CoRR, 2020

Learning from Incomplete Labeled Data via Adversarial Data Generation.

Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning.

Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, Jiliang Tang

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Sequence Learning with Side Dependencies.

Zhiwei Wang, Hui Liu, Gale Yan Huang, Zitao Liu

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Does Gender Matter? Towards Fairness in Dialogue Systems.

Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, Jiliang Tang

Proceedings of the 28th International Conference on Computational Linguistics, 2020

Whole-Chain Recommendations.

Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang

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

Learning Multi-Level Dependencies for Robust Word Recognition.

Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu

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.

Tian Xie, Guan-Hua Tu, Bangjie Yin, Chi-Yu Li, Chunyi Peng, Mi Zhang, Hui Liu, Xiaoming Liu

CoRR, 2018