| Fedprompt: Communication-efficient and privacy-preserving prompt tuning in federated learning H Zhao, W Du, F Li, P Li, G Liu ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 23 | 2023 |
| A Bayesian Possibilistic C-Means clustering approach for cervical cancer screening FQ Li, SL Wang, GS Liu Information Sciences 501, 495-510, 2019 | 18 | 2019 |
| Plmmark: a secure and robust black-box watermarking framework for pre-trained language models P Li, P Cheng, F Li, W Du, H Zhao, G Liu Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14991 …, 2023 | 16 | 2023 |
| Fostering the robustness of white-box deep neural network watermarks by neuron alignment FQ Li, SL Wang, Y Zhu ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 15 | 2022 |
| Leveraging Multi-task Learning for Umambiguous and Flexible Deep Neural Network Watermarking. F Li, L Yang, S Wang, AWC Liew SafeAI@ AAAI, 2022 | 14 | 2022 |
| Online intrusion detection for internet of things systems with full bayesian possibilistic clustering and ensembled fuzzy classifiers FQ Li, RJ Zhao, SL Wang, LB Chen, AWC Liew, W Ding IEEE Transactions on Fuzzy Systems 30 (11), 4605-4617, 2022 | 13 | 2022 |
| Persistent watermark for image classification neural networks by penetrating the autoencoder FQ Li, SL Wang 2021 IEEE International Conference on Image Processing (ICIP), 3063-3067, 2021 | 13 | 2021 |
| Sensor deployment for wireless sensor networks: A conjugate learning automata-based energy-efficient approach C Di, F Li, S Li IEEE Wireless Communications 27 (5), 80-87, 2020 | 13 | 2020 |
| Secure watermark for deep neural networks with multi-task learning F Li, S Wang arXiv preprint arXiv:2103.10021, 2021 | 11 | 2021 |
| Large-scale malicious software classification with fuzzified features and boosted fuzzy random forest FQ Li, SL Wang, AWC Liew, W Ding, GS Liu IEEE Transactions on Fuzzy Systems 29 (11), 3205-3218, 2020 | 11 | 2020 |
| Watermarking protocol for deep neural network ownership regulation in federated learning FQ Li, SL Wang, AWC Liew 2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 1-4, 2022 | 10 | 2022 |
| Towards practical watermark for deep neural networks in federated learning FQ Li, SL Wang, AWC Liew arXiv preprint arXiv:2105.03167, 2021 | 9 | 2021 |
| Regulating ownership verification for deep neural networks: Scenarios, protocols, and prospects FQ Li, SL Wang, AWC Liew arXiv preprint arXiv:2108.09065, 2021 | 8 | 2021 |
| An efficient parameter-free learning automaton scheme C Di, Q Liang, F Li, S Li, F Luo IEEE Transactions on Neural Networks and Learning Systems 32 (11), 4849-4863, 2020 | 6 | 2020 |
| Lip segmentation with muti-scale features based on fully convolution network Z Ju, X Lin, F Li, S Wang 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC …, 2018 | 6 | 2018 |
| Maximizing influence on social networks with conjugate learning automata C Di, F Li, K Qi, S Li 2019 IEEE Global Communications Conference (GLOBECOM), 1-6, 2019 | 4 | 2019 |
| A novel framework for learning automata: a statistical hypothesis testing approach C Di, S Li, F Li, K Qi IEEE Access 7, 27911-27922, 2019 | 4 | 2019 |
| R-Judge: Benchmarking Safety Risk Awareness for LLM Agents T Yuan, Z He, L Dong, Y Wang, R Zhao, T Xia, L Xu, B Zhou, F Li, Z Zhang, ... arXiv preprint arXiv:2401.10019, 2024 | 3 | 2024 |
| Linear Functionality Equivalence Attack Against Deep Neural Network Watermarks and a Defense Method by Neuron Mapping FQ Li, SL Wang, AWC Liew IEEE Transactions on Information Forensics and Security 18, 1963-1977, 2023 | 3 | 2023 |
| Bayesian inference based learning automaton scheme in Q-model environments C Di, F Li, S Li, J Tian Applied Intelligence 51, 7453-7468, 2021 | 2 | 2021 |
