发表论文

2024年

  1. Haoran Li, Long Ma,Haolin Shi, Yanbin Hao, Lechao Cheng, Yong Liao, Pengyuan Zhou, “3D-GOI: 3D GAN Omni-Inversion for Multifaceted and Multi-object Editing”, ECCV 2024 – Proceedings of European Conference on Computer Vision, Milano, Italy, 2024.
  2. Haoran Li, Haolin Shi, Wenli Zhang, Wenjun Wug, Yong Liao, Lin Wang, Lik-Hang LEE, Pengyuan Zhou, “DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling”, ECCV 2024 – Proceedings of European Conference on Computer Vision, Milano, Italy, 2024.
  3. Qinglong Huang, Haoran Li, Yanbin Hao, Yong Liao, Pengyuan Zhou, “Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise”, Proceedings of the 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, 2024.
  4. Wei Tang, Yixin Cao, Jiahao Ying, Bo Wang, Yuyue Zhao, Yong Liao, Pengyuan Zhou, “A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential”, Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, Bangkok, Thailand, 2024.
  5. Botao Xiong, Nan Li,Yong Liao, Pengyuan Zhou. “Gamified Alzheimer’s Disease Diagnosis via Virtual Reality,” 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, Mar 24, 2024, Orlando, Florida USA.
  6. Jianjian Li, Shengwei Liang, Yong Liao, Hongping Deng, Haiyang Yu, “USTCCTSU at SemEval-2024 Task 1: Reducing Anisotropy for Cross-lingual Semantic Textual Relatedness“, 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Mexico City, Mexico.
  7. 林怡航, 周鹏远, 吴治谦, 廖勇, “基于触发器逆向的联邦学习后门防御方法“, 《信息网络安全》, 2024年, 第24卷, 第2期.
  8. Yihang Lin, Yong Liao, Zhiqian Wu, Pengyuan Zhou, “Mitigating Backdoors in Federated Learning with FLD“, 2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT 2024), Nanjing,China.
  9. Hao Liu, Yingguang Yang, Qi Wu, Buyun He, Yong Liao, Pengyuan Zhou, “FacGNN: Multi-Faceted Fairness Enhancement for GNN Through Adversarial and Contrastive Learning“, 2024 International Joint Conference on Neural Networks (IJCNN) – Machine Learning, Pacifico Yokohama, Yokohama, Japan.

2023年

  1. Bingbing Chen and Yong Liao. “Spatio-Temporal Deep Fusion Graph Convolutional Networks for Crime Prediction“. The 7th International Conference on Machine Learning and Soft Computing (ICMLSC 2023)， January 5-7, 2023，Chongqing, China.
  2. Z. Li, S. Feng, J. Shi, Y. Zhou, Y. Liao., “Future event prediction based on temporal knowledge graph embedding,” Computer Systems Science and Engineering, vol. 44, no.3, pp. 2411–2423, 2023.
  3. Yingguang Yang, Renyu Yang, Hao Peng, Yangyang Li, Tong Li, Yong Liao, Pengyuan Zhou, “FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection,” WWW ’23: Proceedings of the ACM Web Conference 2023, April 2023.
  4. Yan Shi, Yao Tian, Chengwei Tong, Chunyan Zhu, Qianqian Li, Mengzhu Zhang, Wei Zhao, Yong Liao, Pengyuan Zhou,,“Detect Depression from Social Networks with Sentiment Knowledge Sharing,”  Social Media Processing. SMP 2023. Communications in Computer and Information Science, vol 1945. Springer, Singapore. https://doi.org/10.1007/978-981-99-7596-9_10.
  5. Reza Hadi Mogavi, Chao Deng, Justin Juho Kim, Pengyuan Zhou, Young D. Kwon, Ahmed Hosny Saleh Metwally, Ahmed Tlili, Simone Bassanelli, Antonio Bucchiarone, Sujit Gujar, Lennart E. Nacke, Pan Hui, “ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions,“ Computers in Human Behavior: Artificial Humans, Volume 2, Issue 1, 2024, ISSN 2949-8821, https://doi.org/10.1016/j.chbah.2023.100027.
  6. Q. Guo, X. Chen, P. Zhou and Y. Liao, “Cross-Domain Data Extraction and Knowledge Graph Construction for Dispute Analysis,” 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS), Hong Kong, Hong Kong, 2023, pp. 959-960, doi: 10.1109/ICDCS57875.2023.00109.
  7. X. Chen, J. Bao, P. Zhou and Y. Liao, “Hierarchical Privacy-Preserved Knowledge Graph,” 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS), Hong Kong, Hong Kong, 2023, pp. 1-2, doi: 10.1109/ICDCS57875.2023.00097.
  8. P. Zhou et al., “Metaverse for Connected and Automated Vehicles and Intelligent Transportation Systems,” in IEEE Vehicular Technology Magazine, vol. 18, no. 4, pp. 19-21, Dec. 2023, doi: 10.1109/MVT.2023.3333444. 
  9. Hengwei Xu, Pengyuan Zhou, Haiyong Xie, Yong Liao, “Mercury: Fast and Optimal Device Placement for Large Deep Learning Models”, ICPP ’23: Proceedings of the 52nd International Conference on Parallel Processing， August 2023， Pages 412–422， https://doi.org/10.1145/3605573.3605603
  10. Shuhao Fu, Yong Liao, Pengyuan Zhou, “Training ChatGPT-like Models with In-network Computation”, APNET ’23: Proceedings of the 7th Asia-Pacific Workshop on Networking, June 2023, Pages 206–207, https://doi.org/10.1145/3600061.3603136.
  11.  Xi Liu, Long Ma, Zhen Chen, Changgang Zheng, Ren Chen, Yong Liao, Shufan Yang, “A Novel State Space Exploration Method for the Sparse-Reward Reinforcement Learning Environment,” In: Bramer, M., Stahl, F. (eds) Artificial Intelligence XL. SGAI 2023. Lecture Notes in Computer Science(), vol 14381. Springer, Cham. https://doi.org/10.1007/978-3-031-47994-6_18
  12. Guo, Qinglang, Yong Liao, Zhe Li, Hui Lin, and Shenglin Liang, “Convolutional Models with Multi-Feature Fusion for Effective Link Prediction in Knowledge Graph Embedding,” Entropy 25, no. 10: 1472. https://doi.org/10.3390/e25101472
  13. Guo, Qinglang, Yong Liao, Zhe Li, and Shenglin Liang, “Multi-Modal Representation via Contrastive Learning with Attention Bottleneck Fusion and Attentive Statistics Features,” Entropy 25, no. 10: 1421. https://doi.org/10.3390/e25101421
  14. Xun Deng, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He, Yong Liao, “Counterfactual Active Learning for Out-of-Distribution Generalization,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, July 2023, Toronto, Canada.

2022年

  1. Renjie Zhou, Zhongyi Xie, Jian Wan, Jilin Zhang, Yong Liao and Qiang Liu. “Attention and Edge-Label Guided Graph Convolutional Networks for Named Entity Recognition”. EMNLP 2022 – The 2022 Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, The United Arab Emirates, December 7–11, 2022.
  2. Wei Tang, Benfeng Xu, Yuyue Zhao, Zhendong Mao, Yifeng Liu, Yong Liao and Haiyong Xie. “UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction”. EMNLP 2022 – The 2022 Conference on Empirical Methods in Natural Language Processing. Abu Dhabi, The United Arab Emirates, December 7–11, 2022.
  3. Mingjie Sun, Pengyuan Zhou, Hui Tian, Yong Liao, Haiyong Xie. “Spatial-Temporal Attention Network for Crime Prediction with Adaptive Graph Learning”. ICANN 2022-The 31st International Conference on Artificial Neural Networks, Bristol (UK), September 6-9, 2022.
  4. Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang. “Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis”. KDD 2022-The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington DC, USA, August 14-18, 2022.
  5. Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao, Yongdong Zhang. “Interpolative Distillation for Unifying Biased and Debiased Recommendation”. SIGIR 2022-The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11-15, 2022.
  6. Pengyuan Zhou, Hengwei Xu, Lik Hang Lee, Pei Fang, Pan Hui. “Are You Left Out?: An Efficient and Fair Federated Learning for Personalized Profiles on Wearable Devices of Inferior Networking Conditions”. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 6, Issue 2, July 2022.
  7. Pengyuan Zhou, Pranvera Kortoci, Yui-Pan Yau, Tristan Braud, Xiujun Wang, Benjamin Finley, Lik-Hang Lee, Sasu Tarkoma, Jussi Kangasharju, Pan Hui. “Augmented Informative Cooperative Perception”. IEEE Transactions on Intelligent Transportation Systems, 2022.
  8. Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Shi Jun, Yongdong Zhang. “Causal Incremental Graph Convolution for Recommender System Retraining”. Special Issue: Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications, IEEE Transactions on Neural Networks and Learning Systems, 2022.
  9. Fangmin Shan, Jun Shi, Zhipeng Li, Yangzhao Yang, Yong Liao. “Research on the Application of EMD Decomposition-based AR Model in Popularity Prediction of Public Sentiment on Events”. In Proceedings of DSDE 2022: International Con-ference on Data Storage and Data Engineering. Sanya, China, Feb. 2022.
  10. Zheng Ma, Zhiqiang Hu, Jun Shi, Zhipeng Li, Yang Zhou, Yong Liao, Yangzhao Yang, Zhenyuan Gao and Jie Zhang. “A module based full cycle construction method of domain-specific knowledge graph”. In Proceedings of the 8th interna-tional conference on artificial intelligence and security (ICAIS 2022). Qinghai, China, July 2022.
  11. Zhiqiang Hu, Zheng Ma, Jun Shi, Zhipeng Li, Yangzhao Yang, Yong Liao, Zhenyuan Gao, Jie Zhang. “A top-down method of extraction Entity Relationship Triples and obtaining annotated data”. In Proceedings of the 8th international con-ference on artificial intelligence and security (ICAIS 2022). Qinghai, China, July 2022.
  12. Yang Zhou, Jun Shi, Zhipeng Li, Yong Liao, Zheng MA, Xuejie Ye and Yang-zhao Yang. “Analysis and Architecture Design of a Large-scale Event-centric Knowledge Graph System for Dispute Resolution”. In Proceedings of the 8th in-ternational conference on artificial intelligence and security (ICAIS 2022). Qinghai, China, July 2022.
  13. Zhipeng Li, Yan Shi, Shanshan Feng, Yong Liao, Jun Shi and Yangzhao Yang. “Future Event Prediction based on Temporal Knowledge Graph Embedding”. In Proceedings of the 8th international conference on artificial intelligence and secu-rity (ICAIS 2022). Qinghai, China, July 2022.
  14. Wenxiao ZHANG, Sikun LIN, Farshid H. BIJARBOONEH, Hao-Fei CHENG, Tristan BRAUD, Pengyuan ZHOU, Lik-Hang LEE, and Pan HUI. “EdgeXAR: A 6-DoF Camera Multi-target Interaction Framework for MAR with User-friendly Latency Compensation”. In Proceedings of the ACM on Human-Computer Interaction (PACM HCI) and the 14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS), Sophia Antipolis, France, June 2022.
  15. 李志鹏，杨阳朝，廖勇，俞能海，吴哲，谢海永，石珺。 “数据驱动的事件预测技术最新研究进展”。 《信息安全学报》

2021年

  1. 王静，钟瑶，卢瑶，陈冰冰，易勇。 “美军通信网络与信息系统发展研究综述”。 《中国电子科学研究院学报》，Vol. 16，No. 11，2021年11月，doi: 10.3969/j.issn. 1673-5692.2021.11.004。
  2. Aleksandr Zavodovski, Lorenzo Corneo, Nitinder Mohan, Suzan Bayhan, Pengyuan Zhou, Walter Wong, Andreas Johnsson, Jussi Kangasharju, “Decentralizing Computation with Edge Computing: Potential and Challenges”, ACM CoNEXT 2021 Interdisciplinary Workshop on (de)Centralization in the Internet (ACM IWCI 2021).
  3. Lik-Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang, Dianlei Xu, Zijun Lin, Abhishek Kumar, CarlosBermejo, and Pan Hui, “All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity,Virtual Ecosystem, and Research Agenda”, http://dx.doi.org/10.13140/RG.2.2.11200.05124/8.
  4. Hangjing Zhang, Yuejiang Li, Yan Chen, H. Vicky Zhao, “Smart Evolution for Information Diffusion Over Social Networks”, IEEE Transactions on Information Forensics and Security, vol.16, pp. 1203-1217, 2021.
  5. Dongheng Zhang, Yang Hu, Yan Chen, “MTrack: Tracking Multi-Person Moving Trajectories and Vital Signs with Radio Signals”, IEEE Internet of Things Journal, vol. 8, no. 5, pp. 3904-3914, March 2021.
  6. Yan Chen, Hongyu Deng, Dongheng Zhang, Yang Hu, “SpeedNet: Indoor Speed Estimation with Radio Signals”, IEEE Internet of Things Journal, vol. 8, no. 4, pp. 2762-2774, Feb. 2021.
  7. Xueqi Zhang, Haiyong Xie, Hui Lin.  “HOPE-L: A Lossless Database Watermarking Method in Homomorphic Encryption Domain”. International Conference on Smart City and Informatization. 2021.
  8. Xueqi Zhang, Shuo Wang, Chenyu Liu, Min Zhang, Xiaohan Liu, Haiyong Xie. “Thinking in Patch: Towards Generalizable Forgery Detection with Patch Transformation”. The Pacific Rim International Conferences on Artificial Intelligence (PRICAI). 2021.

2020年

  1. Yan Chen, Xiang Su, Yang Hu, Bing Zeng, “Residual Carrier Frequency Offset Estimation and Compensation for Commodity WiFi”, IEEE Transactions on Mobile Computing, vol. 19, no. 12, pp. 2891-2902, Dec. 2020。
  2. Ying He, Yan Chen, Yang Hu, and Bing Zeng, “WiFi Vision: Sensing, Recognition, and Detection With Commodity MIMO-OFDM WiFi”, IEEE Internet of Things Journal, vol. 7, no. 9, pp. 8296-8317, Sept 2020.
  3. Yan Chen, Hangjing Zhang, Yang Hu, Optimal Power and Bandwidth Allocation for Multiuser Video Streaming in UAV Relay Networks, IEEE Transactions on Vehicular Technology, vol. 69, no. 6, pp. 6644-6655, June 2020.
  4. Chaofan He, Yang Hu, Yan Chen, Xiaopeng Fan, Houqiang Li, Bing Zeng, MUcast: Linear Uncoded Multiuser Video Streaming with Channel Assignment and Power Allocation Optimization, IEEE Transactions on Circuits and Systems for Video Technology (CSVT), vol.30, no.4, pp.1136-1146, April 2020.
  5. Dongheng Zhang, Yang Hu, Yan Chen, Bing Zeng, Calibrating Phase Offsets for Commodity WiFi, IEEE Systems Journal, vol. 14, no.1, pp. 661-664, March 2020.

2019年

  1. Jian Ni, Shanghang Zhang, and Haiyong Xie. Dual adversarial semantics-consistent network for generalized zero-shot learning. Advances in Neural Information Processing Systems 32, pp. 6146–6157. 2019.
  2. Yan Chen, Xuanyu Cao, K. J. Ray Liu, Community Detection in Networks: A Game-Theoretic Framework, EURASIP Journal on Advances in Signal Processing (2019) 2019.
  3. Wei Li, Meng-Lin Ku, Yan Chen, Yichen Wang, and Zhonghua Liang, Transmission Policy of Two-Way Relay Networks With Multiple Stochastic Energy Harvesting Nodes, IEEE ACESS, vol. 7, no.1, pp. 76967-76984, Dec. 2019.
  4. Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng & Tat-Seng Chua, Neural Graph Collaborative Filtering, SIGIR 2019.
  5. Xin Xin, Xiangnan He*, Yongfeng Zhang, Yongdong Zhang & Joemon Jose, Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation, SIGIR 2019.