Fangqi Li

According to our database, Fangqi Li authored at least 32 papers between 2016 and 2024.

Collaborative distances:

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

2024

R-Judge: Benchmarking Safety Risk Awareness for LLM Agents.

Tongxin Yuan, Zhiwei He, Lingzhong Dong, Yiming Wang, Ruijie Zhao, Tian Xia, Lizhen Xu, Binglin Zhou, Fangqi Li, Zhuosheng Zhang, Rui Wang, Gongshen Liu

CoRR, 2024

Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond.

Fangqi Li, Haodong Zhao, Wei Du, Shilin Wang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learning automata-accelerated greedy algorithms for stochastic submodular maximization.

Chong Di, Fangqi Li, Pengyao Xu, Ying Guo, Chao Chen, Minglei Shu

Knowl. Based Syst., December, 2023

Measuring and Understanding Crowdturfing in the App Store.

Qinyu Hu, Xiaomei Zhang, Fangqi Li, Zhushou Tang, Shilin Wang

Inf., 2023

FedPrompt: Communication-Efficient and Privacy-Preserving Prompt Tuning in Federated Learning.

Haodong Zhao, Wei Du, Fangqi Li, Peixuan Li, Gongshen Liu

Proceedings of the IEEE International Conference on Acoustics, 2023

PLMmark: A Secure and Robust Black-Box Watermarking Framework for Pre-trained Language Models.

Peixuan Li, Pengzhou Cheng, Fangqi Li, Wei Du, Haodong Zhao, Gongshen Liu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Solving the Capsulation Attack against Backdoor-based Deep Neural Network Watermarks by Reversing Triggers.

Fangqi Li, Shilin Wang, Yun Zhu

CoRR, 2022

Reduce Communication Costs and Preserve Privacy: Prompt Tuning Method in Federated Learning.

Haodong Zhao, Wei Du, Fangqi Li, Peixuan Li, Gongshen Liu

CoRR, 2022

Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks.

Fangqi Li, Shilin Wang

CoRR, 2022

Leveraging Multi-task Learning for Umambiguous and Flexible Deep Neural Network Watermarking.

Fangqi Li, Lei Yang, Shilin Wang, Alan Wee-Chung Liew

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022) co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022), 2022

2021

An Efficient Parameter-Free Learning Automaton Scheme.

Chong Di, Qilian Liang, Fangqi Li, Shenghong Li, Fucai Luo

IEEE Trans. Neural Networks Learn. Syst., 2021

FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks.

Runbo Ni, Xueyan Li, Fangqi Li, Xiaofeng Gao, Guihai Chen

CoRR, 2021

Regulating Ownership Verification for Deep Neural Networks: Scenarios, Protocols, and Prospects.

Fangqi Li, Shi-Lin Wang, Alan Wee-Chung Liew

CoRR, 2021

Towards Practical Watermark for Deep Neural Networks in Federated Learning.

Fangqi Li, Shi-Lin Wang

CoRR, 2021

Secure Watermark for Deep Neural Networks with Multi-task Learning.

Fangqi Li, Shilin Wang

CoRR, 2021

Bayesian inference based learning automaton scheme in Q-model environments.

Chong Di, Fangqi Li, Shenghong Li, Jianwei Tian

Appl. Intell., 2021

2020

Sensor Deployment for Wireless Sensor Networks: A Conjugate Learning Automata-Based Energy-Efficient Approach.

Chong Di, Fangqi Li, Shenghong Li

IEEE Wirel. Commun., 2020

Evaluation and Comparison of Diffusion Models with Motif Features.

Fangqi Li

CoRR, 2020

Influence Maximization on Dynamic Social Networks with Conjugate Learning Automata.

Fangqi Li, Chong Di, Shenghong Li

CoRR, 2020

Solving the Three-Player-Game.

Fangqi Li

CoRR, 2020

The Electromagnetic Balance Game: A Probabilistic Perspective.

Fangqi Li

CoRR, 2020

On the Submodularity of Diffusion Models: Equivalent Conditions and Applications.

Fangqi Li, Chong Di, Wenwen Xia

CoRR, 2020

Gaussian Process Bandits for Online Influence Maximization.

Wenwen Xia, Fangqi Li, Shenghong Li

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

2019

A Bayesian Possibilistic C-Means clustering approach for cervical cancer screening.

Fangqi Li, Shi-Lin Wang, Gongshen Liu

Inf. Sci., 2019

A Novel Framework for Learning Automata: A Statistical Hypothesis Testing Approach.

Chong Di, Shenghong Li, Fangqi Li, Kaiyue Qi

IEEE Access, 2019

Maximizing Influence on Social Networks with Conjugate Learning Automata.

Chong Di, Fangqi Li, Kaiyue Qi, Shenghong Li

Proceedings of the 2019 IEEE Global Communications Conference, 2019

2018

Laplace Exponential Family PCA.

Fangqi Li, Xudie Ren

Proceedings of the Intelligent Computing Theories and Application, 2018

Lip Segmentation with Muti-scale Features Based on Fully Convolution Network.

Zhen Ju, Xiang Lin, Fangqi Li, Shilin Wang

Proceedings of the Third IEEE International Conference on Data Science in Cyberspace, 2018

A Multi-view Deep Learning Approach for Detecting Threats on 3D Human Body.

Zhicong Yan, Shuai Feng, Fangqi Li, Zhengwu Xu, Shenghong Li

Proceedings of the Communications, Signal Processing, and Systems, 2018

An Efficient Classification Method of Uncertain Data with Sampling.

Jinchao Huang, Yulin Li, Kaiyue Qi, Fangqi Li

Proceedings of the Communications, Signal Processing, and Systems, 2018

2017

Probabilistic Model of Object Detection Based on Convolutional Neural Network.

Fangqi Li, Xu-Die Ren, Hao-Nan Guo

Proceedings of the Communications, Signal Processing, and Systems, 2017

2016

Gaussian Iteration: A Novel Way to Collaborative Filtering.

Xiaochun Li, Fangqi Li, Ying Guo, Jinchao Huang

Proceedings of the Intelligent Computing Methodologies - 12th International Conference, 2016