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  1. Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang, Yichen Wang, Chen Liu, Yu Lan, Chao Shen. Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models, NeurIPS 2024. (人工智能顶会,CCF A)
  2. Xiaoming Liu, Chen Liu, Zhaohan Zhang, Chengzhengxu Li, Longtian Wang, Yu Lan, Chao Shen. StablePT: Towards Stable Prompting for Few-shot Learning via Input Separation, EMNLP 2024.(自然语言处理顶会,CCF B)
  3. Wang, Yichen and Feng, Shangbin and Hou, Abe Bohan and Pu, Xiao and Shen, Chao and Liu, Xiaoming and Tsvetkov, Yulia and He, Tianxing. (2024). Stumbling Blocks: Stress Testing the Robustness of Machine-Generated Text Detectors Under Attacks. ACL 2024. (自然语言处理顶会,CCF A
  4. Liu, S., Liu, X*., Wang, Y., Cheng, Z., Li, C., Zhang, Z., ... & Shen, C. (2024). Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better. ACL 2024. (自然语言处理顶会,CCF A
  5. Li, Chengzhengxu, Xiaoming Liu*, Yichen Wang, Duyi Li, Yu Lan, and Chao Shen. "Dialogue for Prompting: a Policy-Gradient-Based Discrete Prompt Optimization for Few-shot Learning." AAAI 2024 CCF A,Acceptance rate  23.75%[Paper] [Codes]
  6. Yichen Wang, Kevin Yang, Xiaoming Liu, Dan Klein. Improving Pacing in Long-Form Story Planning. EMNLP 2023 Findings. (自然语言处理顶会,CCF B)[Paper] [Codes]
  7. Xiaoming Liu*, Zhaohan Zhang*, Yichen Wang*, Hang Pu, Yu Lan, and Chao Shen. CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Low Resource With Contrastive Learning. EMNLP 2023 Long Paper.(* All the authors contributed equally to this work,自然语言处理顶会,CCF B, Acceptance rate 21.3%[Paper] [Codes] [Data]
  8. Xiaoming Liu, Shaocong Wu, Zhaohan Zhang and Chao Shen, Unify Local and Global Information for Top-N Recommendation,  In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1262-1272. 2022. (CCF A, Full Paper, Accepted rate 161/794=20%)[Paper]   [Codes] 
  9. Li, Q.*, Liu, X.*, Shen, C., Peng, X., Zhou, Y. and Guan, X., 2020. Learning Graph Embedding with Limited Labeled Data: An Efficient Sampling Approach. arXiv preprint arXiv:2003.06100. (* Both authors contributed equally to this work)
  10. Liu, X., Shen, C., Fan, Y., Liu, X., Zhou, Y., & Guan, X. (2018, December). A Co-Evolutionary Model for Inferring Online Social Network User Behaviors. In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) (pp. 85-90). IEEE. (Best Student Paper Award)
  11.  Liu, X., Zhou, Y., Hu, C., Guan, X., & Leng, J. (2014, April). Detecting community structure for undirected big graphs based on random walks. In Proceedings of the 23rd International Conference on World Wide Web (pp. 1151-1156). (CCF A, Workshop on Big Graph Minng)
  12. Liu, X., Zhou, Y., Hu, C., Guan, X., & Sun, X. (2015, July). A feasible graph partition framework for random walks implemented by parallel computing in big graph. In 2015 34th Chinese Control Conference (CCC) (pp. 4986-4991). IEEE.

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  1. Yu Lan, Qiaozhu Zhai, Xiaoming Liu, Xiaohong Guan. Gradient accelerated stochastic dual dynamic programming for economic dispatch in microgrids with energy storages, Journal of Energy Storage,2024.
  2. 刘晓明, 李丞正旭, 吴少聪, 张宇辰, 白红艳, 程泽华, 陈 卓,李永峰 兰钰,沈超.  文本分类算法及其应用场景研究综述,  计算机学报,2024 06. (CCF T1)
  3. Yu Lan, Qiaozhu Zhai, Xiaoming Liu, Xiaohong Guan; First Order Accelerated Robust Dual Dynamic Programming for Robust Economic Dispatch, IEEE Transactions on Power Systems. 2024.(电力系统顶刊,SCI, IF=7.326
  4. Yu Lan, Qiaozhu Zhai, Xiaoming Liu, and Xiaohong Guan. "Robust Approximate Dynamic Programming for Large-scale Unit Commitment with Energy Storages." IEEE Transactions on Automation Science and Engineering (2023).
  5. Yu Lan, Qiaozhu Zhai, Xiaoming Liu, and Xiaohong Guan. "Fast Stochastic Dual Dynamic Programming for Economic Dispatch in Distribution Systems." IEEE Transactions on Power Systems (2022).(电力系统顶刊,SCI, IF=7.326
  6. Xiaoming Liu, Zhanwei Zhang, Lingjuan Lyu, Zhaohan Zhang, Shuai Xiao, Chao Shen, and Philip S. Yu. Traffic anomaly prediction based on joint static-dynamic spatio-temporal evolutionary learning [J]. IEEE Transactions on Knowledge and Data Engineering, 2022. SCI IF 6.977, JCR分区:Q1, CCF A[Paper] [Codes]
  7. Zhou, Yadong, Zhihao Ding, Xiaoming Liu*, Chao Shen, Lingling Tong, and Xiaohong Guan. "Infer-AVAE: An attribute inference model based on adversarial variational autoencoder." Neurocomputing 483 (2022): 105-115.
  8. 刘晓明、张兆晗、杨晨阳、张宇辰、沈超、周亚东、管晓宏,在线社交网络文本内容对抗技术,计算机学报.中文CCF A【论文】
  9. Zhou, Yadong, Tianyi Yue, Xiaoming Liu, Chao Shen, Lingling Tong, and Zhihao Ding. "Payment-Guard: Detecting fraudulent in-app purchases in iOS system." Neurocomputing 422 (2021): 263-276.
  10.  Liu, X., Lan Y., Shen, C., Zhou, Y.,  & Guan, X. A Real-time Explainable Traffic Collision Inference Framework Based on Probabilistic Graph Theory. Knowledge-Based Systems. 2020. (SCI  IF 5.921, 中科院分区:1区,CCF C );
  11.  Liu X, Shen C, Wang W, Guan X. CoEvil: A Co-Evolutionary Model for Crime Inference Based on Fuzzy Rough Feature Selection. IEEE Transactions on Fuzzy Systems. 2019 Sep 6. (SCI  IF 8.759,  中科院分区:1CCF B );
  12. Liu, X., Shen, C., Guan, X., & Zhou, Y. (2018). Digger: Detect Similar Groups in Heterogeneous Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD)13(1), 1-27. (SCI IF 1.895, 中科院分区:3区, CCF B)
  13. Liu, X., Shen, C., Guan, X., & Zhou, Y. (2018). We know who you are: Discovering similar groups across multiple social networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems (SCI  IF 7.351, 中科院:1CCF B )
  14. Liu, X., Zhou, Y., Guan, X., & Shen, C. (2017). A feasible graph partition framework for parallel computing of big graph. Knowledge-Based Systems134, 228-239. (SCI  IF 5.101, 中科院分区:1区, CCF C);
  15. Liu, X., Zhou, Y., Hu, C., & Guan, X. (2016). MIRACLE: A multiple independent random walks community parallel detection algorithm for big graphs. Journal of Network and Computer Applications70, 89-101. (SCI IF 5.273, 中科院分区:1CCF C);
  16. 周亚东, 刘晓明, 杜友田, 管晓宏, & 刘霁. (2015). 一种网络话题的内容焦点迁移识别方法计算机学报38(2), 261-271.