• CORE A*/CCF-A/Q1 Papers (100+): (NeurIPS, ICML, ICLR) x31, (AAAI, IJCAI) x18, (KDD, WWW) x22, (ACL, EMNLP) x10, (SIGMOD, VLDB, ICDE) x7, (IEEE Journal) x22, etc.
• Highlights: Oral/Spotlight Paper (NeurIPS'22/25, ICML'24, ICLR'24/25, AAAI'25/26, ACL'25), Most Influential Paper (IJCAI'21/23), AAAI Innovative Application Award (AAAI'23/25)
• The full list of my publications (with arXiv papers) can be found at Google Scholar.

AI, ML, DM: Time Series, Education, Forecasting, Anomaly Detection, LLM, AI Agent, RCA, AIOps, GNN, SSL, XAI, etc. (* indicates the corresponding author)

• [C127] [KDD'26] Xiaolong Wang, Zhe Zhao, Song Lai, Chaoli Zhang, Zijie Geng, Yu Tong, Ye Wei*, Qingsong Wen*, "From Memorization to Creation: Evaluating the Cognitive Depth of LLM‑Generated Educational Questions," in 32nd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2026), Jeju, Korea, Aug. 2026. (Datasets and Benchmarks Track)
• [C126] [KDD'26] Jiaxi Hu, Disen Lan, Ziyu Zhou, Gefeng Luo, Qingsong Wen, Yuxuan Liang, "How to Train Your Mamba for Time Series Forecasting," in 32nd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2026), Jeju, Korea, Aug. 2026. (Research Track)
• [C125] [KDD'26] Xinyun Zhou, Xinfeng Li, Yinan Peng, Ming Xu, Xuanwang Zhang, Miao Yu, Yidong Wang, Xiaojun Jia, Kun Wang, Qingsong Wen, XiaoFeng Wang, Wei Dong, "Evaluating RAG Robustness to Symbolic Perturbations," in 32nd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2026), Jeju, Korea, Aug. 2026. (Research Track)
• [C124] [KDD'26] Fan Xu, Wei Gong, Hao Wu, Lilan Peng, Nan Wang, Qingsong Wen, Xian Wu, Kun Wang, Xibin Zhao, "Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODE," in 32nd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2026), Jeju, Korea, Aug. 2026. (Research Track)
• [C123] [AAAI'26] Ruijia Zhang, Xinyan Zhao, Ruixiang Wang, Sigen Chen, Guibin Zhang, An Zhang, Kun Wang, Qingsong Wen, "SafeSieve: From Heuristics to Experience in Progressive Pruning for LLM-based Multi-Agent Communication," in 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, Jan. 2026. [paper]
• [C122] [AAAI'26] Sisuo Lyu, Siru Zhong, Weilin Ruan, Qingxiang Liu, Qingsong Wen, Hui Xiong, Yuxuan Liang, "OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting," in 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, Jan. 2026. [paper]
• [C121] [AAAI'26] Shiyuan Li, Yixin Liu, Qingsong Wen, Chengqi Zhang, Shirui Pan, "Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation," in 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, Jan. 2026. [paper] (AAAI Oral, Top 5%)
• [C120] [AAAI'26] Yuan Gao, Ruiqi Shu, Hao Wu, Fan Xu, Yanfei Xiang, Ruijian Gou, Qingsong Wen, Xian Wu, Kun Wang, Xiaomeng Huang, "NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation," in 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, Jan. 2026. [paper]
• [C119] [ADMA'25] Xinliang Zhou, Jianheng Zhou, Jiaping Xiao, Yingwei Zhang, Xiaoshuai Hao, Jing Wang, Badong Chen, Qingsong Wen*, "RPGCN: Relational Probabilistic Graphs for EEG-Based Emotion Mining," in 21st International Conference on Advanced Data Mining and Applications (ADMA 2025), Kyoto, Japan, Oct. 2025. [paper] (ADMA Best Special Session Paper Award)
• [C118] [NeurIPS'25] Jiaxi Hu, Yongqi Pan, Jusen Du, Disen Lan, Xiaqiang Tang, Qingsong Wen, Yuxuan Liang, Weigao Sun, "Improving Nonlinear RNN with Closed-loop Control," in 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA, Dec. 2025. [arXiv] (NeurIPS Spotlight, Top 3.5%)
• [C117] [NeurIPS'25] Zhongzheng Qiao, Chenghao Liu, Yiming Zhang, Ming Jin, Quang Pham, Qingsong Wen, Ponnuthurai Nagaratnam Suganthan, Xudong Jiang, Savitha Ramasamy, "Multi-Scale Finetuning for Encoder-based Time Series Foundation Models," in 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA, Dec. 2025. [arXiv]
• [C116] [NeurIPS'25] Guiyao Tie, Zenghui Yuan, Zeli Zhao, Chaoran Hu, Tianhe Gu, Ruihang Zhang, Sizhe Zhang, Junran Wu, Xiaoyue Tu, Ming Jin, Qingsong Wen, Lixing Chen, Pan Zhou, Lichao Sun, "Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs," in 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA, Dec. 2025. [arXiv]
• [C115] [NeurIPS'25] Zhuohao Yu, Xingru Jiang, Weizheng Gu, Yidong Wang, Qingsong Wen, Shikun Zhang, Wei Ye, "SAEMark: Steering Personalized Multilingual LLM Watermarks with Sparse Autoencoders," in 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA, Dec. 2025. [paper]
• [C114] [NeurIPS'25] Bosong Huang, Ming Jin, Yuxuan Liang, Johan Barthelemy, Debo Cheng, Qingsong Wen, Chenghao Liu, Shirui Pan, "ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models," in 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, USA, Dec. 2025. [arXiv]
• [C113] [EMNLP'25] Zhendong Chu, Jian Xie, Shen Wang, Zichao Wang, Qingsong Wen*, "UniEDU: Toward Unified and Efficient Large Multimodal Models for Educational Tasks," in the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025), Suzhou, China, Nov. 5-9, 2025. (EMNLP Industry) [arXiv]
• [C112] [EMNLP'25] Jingheng Ye, Shen Wang, Deqing Zou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen*, "Position: LLMs Can be Good Tutors in Foreign Language Education," in the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025), Suzhou, China, Nov. 5-9, 2025. (EMNLP Main) [arXiv]
• [C111] [EMNLP'25] Hanjun Luo, Yingbin Jin, Xinfeng Li, Xuecheng Liu, Ruizhe Chen, Tong Shang, Kun Wang, Qingsong Wen, Zuozhu Liu, "DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition," in the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025), Suzhou, China, Nov. 5-9, 2025. (EMNLP Main) [arXiv]
• [C110] [EMNLP'25] Zhendong Chu, Shen Wang, Jian Xie, Tinghui Zhu, Yibo Yan, Jinheng Ye, Aoxiao Zhong, Xuming Hu, Jing Liang, Philip S. Yu, Qingsong Wen*, "LLM Agents for Education: Advances and Applications," in the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025), Suzhou, China, Nov. 5-9, 2025. (EMNLP Findings) [arXiv]
• [C109] [MM'25] YiFan Zhang, Yang Shi, Weichen Yu, Qingsong Wen*, Xue Wang, Wenjing Yang, Zhang Zhang, Liang Wang, Rong Jin, "Debiasing Multimodal Large Language Models via Penalization of Language Priors," in the 33rd ACM International Conference on Multimedia (MM 2025), Dublin, Ireland, Oct. 27-31, 2025. [arXiv] [code]
• [C108] [MM'25] Feiran Liu, Yuzhe Zhang, Xinyi Huang, Yinan Peng, Xinfeng Li, Lixu Wang, Yutong Shen, Ranjie Duan, Simeng Qin, Xiaojun Jia, Qingsong Wen, Wei Dong, "The Eye of Sherlock Holmes: Uncovering User Private Attribute Profiling via Vision-Language Model Agentic Framework," in the 33rd ACM International Conference on Multimedia (MM 2025), Dublin, Ireland, Oct. 27-31, 2025. [arXiv]
• [C107] [ACL'25] Yibo Yan, Shen Wang, Jiahao Huo, Philip S. Yu, Xuming Hu*, Qingsong Wen*, "MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection," in the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, Jul. 27 - Aug. 1, 2025. (ACL Industry Oral). [arXiv]
• [C106] [ACL'25] Hang Li, Tianlong Xu, Kaiqi Yang, Yucheng Chu, Yanling Chen, Yichi Song, Qingsong Wen, Hui Liu, "Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions," in the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, Jul. 27 - Aug. 1, 2025. (ACL Main). [arXiv]
• [C105] [ACL'25] Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, Wenjie Du, Stefan Zohren, Zhangyang Wang, Ming Jin*, Qingsong Wen*, "Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement," in the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, Jul. 27 - Aug. 1, 2025. (ACL Main). [arXiv]
• [C104] [ACL'25] Miao Yu, Shilong Wang, Guibin Zhang, Junyuan Mao, Chenlong Yin, Qijiong Liu, Kun Wang, Qingsong Wen, Yang Wang, "NetSafe: Exploring the Topological Safety of Multi-agent System," in the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, Jul. 27 - Aug. 1, 2025. (ACL Findings). [arXiv]
• [C103] [ACL'25] Yibo Yan, Jiamin Su, Jianxiang He, Fangteng FU, Xu Zheng, Yuanhuiyi Lyu, Kun Wang, Shen Wang, Qingsong Wen, Xuming Hu, "A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges," in the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, Jul. 27 - Aug. 1, 2025. (ACL Findings). [arXiv]
• [C102] [ECML-PKDD'25] Kexin Zhang, Baoyu Jing, K. Selçuk Candan, Dawei Zhou, Qingsong Wen, Han Liu, Kaize Ding, "Cross-Domain Conditional Diffusion Models for Time Series Imputation," in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2025), Porto, Portugal, Sep. 2025. [arXiv]
• [C101] [KDD'25] Shiyu Wang, Wei Lu, Jiawei LI, Xiaoming Shi, Xinyue Zhong, Zhou Ye, Ming Jin, Qingsong Wen, "FRT: Flow-based Reconcile Transformer for Hierarchical Time Series," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Applied Data Science Track)
• [C100] [KDD'25] Qiming Chen, Yingying ZHANG, Qingsong Wen, Liang Sun, "EMD-Period: Detecting Multi-periodicity in Industrial Cloud Clusters via Time-Frequency Decomposition," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Applied Data Science Track)
• [C99] [KDD'25] Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Yuxuan Liang, Yu Zheng, Qingsong Wen, Kun Wang, "DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Applied Data Science Track) [arXiv]
• [C98] [KDD'25] Yingtao Luo, Shikai Fang, Binqing Wu, Qingsong Wen, Liang Sun, "Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Research Track) [arXiv]
• [C97] [KDD'25] Yaxuan Wang, Hao Cheng, Jing Xiong, Qingsong Wen, Han Jia, Ruixuan Song, Liyuan Zhang, Zhaowei Zhu, Yang Liu, "Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Research Track) [arXiv] [code]
• [C96] [KDD'25] Miao Yu, Fanci Meng, Xinyun Zhou, Shilong Wang, Junyuan Mao, Linsey Pang, Tianlong Chen, Kun Wang, Xinfeng Li*, Yongfeng Zhang, Bo An, Qingsong Wen*, "A Survey on Trustworthy LLM Agents: Threats and Countermeasures," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Survey) [arXiv]
• [C95] [KDD'25] Yuxuan Liang, Haomin Wen, Yutong Xia, Ming Jin, Bin Yang, Flora Salim, Qingsong Wen, Shirui Pan, Gao Cong, "Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Survey) [arXiv]
• [C94] [KDD'25] Kun Yi, Qi Zhang, Wei Fan, Longbing Cao, Shoujin Wang, Guodong Long, Liang Hu, Hui He, Qingsong Wen, Hui Xiong, "A Survey on Deep Learning based Time Series Analysis with Frequency Transformation," in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025. (Survey) [arXiv]
• [C93] [ICML'25] Siru Zhong, Weilin Ruan, Ming Jin, Huan Li, Qingsong Wen, Yuxuan Liang, "Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting," in the International Conference on Machine Learning (ICML 2025), Vancouver, Canada, July 13-19, 2025. [arXiv]
• [C92] [ICML'25] Yuan Gao, Hao Wu, Ruiqi Shu, Huanshuo Dong, Fan Xu, Rui Chen, Yibo Yan, Qingsong Wen, Xuming Hu, Kun Wang, Jiahao Wu, Qing Li, Hui Xiong, Xiaomeng Huang, "OneForecast: A Universal Framework for Global and Regional Weather Forecasting," in the International Conference on Machine Learning (ICML 2025), Vancouver, Canada, July 13-19, 2025. [arXiv]
• [C91] [ICLR'25] Xiaoming Shi, Shiyu Wang, Yuqi Nie, Dianqi Li, Zhou Ye, Qingsong Wen*, Ming Jin*, "Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts," in the International Conference on Learning Representations (ICLR 2025), Singapore, Apr. 2025. [arXiv] [code] (ICLR Spotlight, Top 5%)
• [C90] [ICLR'25] YiFan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen*, Zhang Zhang*, Liang Wang, Rong Jin, "MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?" in the International Conference on Learning Representations (ICLR 2025), Singapore, Apr. 2025. [arXiv] [code]
• [C89] [ICLR'25] Zaige Fei, Fan Xu, Junyuan Mao, Yuxuan Liang, Qingsong Wen, Kun Wang, Hao Wu, Yang Wang, "Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics," in the International Conference on Learning Representations (ICLR 2025), Singapore, Apr. 2025. [paper]
• [C88] [IJCAI'25] Jun Wang, Wenjie Du, Yiyuan Yang, Linglong Qian, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, Qingsong Wen*, "Deep Learning for Multivariate Time Series Imputation: A Survey", in the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025), Montreal, Canada, Aug. 2025. [arXiv]
• [C87] [IJCAI'25] Weiqi Chen, Zhaoyang Zhu, Yifan Zhang, Lefei Shen, Linxiao Yang, Qingsong Wen, Liang Sun, "Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting", in the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025), Montreal, Canada, Aug. 2025.
• [C86] [CAI'25] Richard J. Tong, Haoyang Li, Sridhar Raghavan, Qingsong Wen, Shannon Gray, Anand Paul, Joleen Liang, Janusz Zalewski, Yacheng Yang, George Tambouratzis, Boon Chong Ang, "IEEE AI Standards for Agentic Systems," in the 2025 IEEE Conference on Artificial Intelligence (IEEE CAI 2025), Santa Clara, USA, May 2025.
• [C85] [VLDB'25] Zhihao Zhuang, Yingying Zhang, Kai Zhao, Chenjuan Guo, Bin Yang, Qingsong Wen, Lunting Fan, "Noise Matters: Cross Contrastive Learning for Flink Anomaly Detection," in the International Conference on Very Large Data Bases (VLDB 2025), London, United Kingdom, Sep. 2025.
• [C84] [VLDB'25] Biao Ouyang, Yingying Zhang, Hanyin Cheng, Yang Shu, Chenjuan Guo, Bin Yang, Qingsong Wen, Lunting Fan, Christian S. Jensen, "RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems," in the International Conference on Very Large Data Bases (VLDB 2025), London, United Kingdom, Sep. 2025. [paper]
• [C83] [AAAI'25] Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen, "Unlocking the Power of LSTM for Long Term Time Series Forecasting," in 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025), Philadelphia, PA, USA, Mar. 2025. [paper] (AAAI Oral, Top 5%)
• [C82] [AAAI'25] Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, Yuxuan Liang, "UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction," in 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025), Philadelphia, PA, USA, Mar. 2025. (AISI Track) [paper]
• [C81] [AAAI'25] Tianlong Xu, YiFan Zhang, Zhendong Chu, Shen Wang, Qingsong Wen*, "AI-Driven Virtual Teacher for Enhanced Educational Efficiency: Leveraging Large Pretrain Models for Autonomous Error Analysis and Correction," in 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025), Philadelphia, PA, USA, Mar. 2025. (IAAI Track) [arXiv] (AAAI/IAAI 2025 Innovative Application Award)
• [C80] [AAAI'25] Hang Li, Tianlong Xu, Ethan Chang, Qingsong Wen*, "Knowledge Tagging with Large Language Model based Multi-Agent System," in 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025), Philadelphia, PA, USA, Mar. 2025. (IAAI Track). [arXiv] (AAAI/IAAI 2025 Innovative Application Award)
• [C79] [ICASSP'25] Gouheng Zhao, Kai Ying, Qingsong Wen, Junwen Zhang, Lin Gui, "Transfer Learning with Transformer and LSTM for Digital Pre-distortion of Terahertz/mmWave Transceiver," in IEEE 50th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025), Hyderabad, India, April 2025.
• [C78] [NeurIPS'24] Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang, "Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv]
• [C77] [NeurIPS'24] Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash, "Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. (D&B Track) [arXiv]
• [C76] [NeurIPS'24] Zhixian Wang, Linxiao Yang, Liang Sun, Qingsong Wen, Yi Wang, "Task-oriented Time Series Imputation Evaluation via Generalized Representers," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv] [code]
• [C75] [NeurIPS'24] Jiaxi Hu, Yuehong HU, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang, "Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv]
• [C74] [NeurIPS'24] Hezhe Qiao, Qingsong Wen, Xiaoli Li, Ee-Peng Lim, Guansong Pang, "Generative Semi-supervised Graph Anomaly Detection," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv]
• [C73] [NeurIPS'24] Cheng Li, Damien Teney, Linyi Yang, Qingsong Wen, Xing Xie, Jindong Wang, "CulturePark: Boosting Cross-cultural Understanding in Large Language Models," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv]
• [C72] [NeurIPS'24] Yidong Wang, Qi Guo, Wenjin Yao, Hongbo Zhang, Xin Zhang, Zhen Wu, Meishan Zhang, Xinyu Dai, Min Zhang, Qingsong Wen, Wei Ye, Shikun Zhang, Yue Zhang, "AutoSurvey: Large Language Models Can Automatically Write Surveys," in 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec. 2024. [arXiv] [code]
• [C71] [EMNLP'24] Xuanwang Zhang, Yunze Song, Yidong Wang, Shuyun Tang, Xinfeng Li, Zhengran Zeng, Zhen Wu, Wei Ye, Wenyuan Xu, Yue Zhang, Xinyu Dai, Shikun Zhang, Qingsong Wen, "RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation," in the 2024 Conference on Empirical Methods in Natural Language Processing System (EMNLP 2024), Miami, USA, Nov. 2024. (Demo Track) [arXiv] [code]
• [C70] [CIKM'24] Zefan Wang, Zichuan Liu, Yingying Zhang, Aoxiao Zhong, Jihong Wang, Fengbin Yin, Lunting Fan, Lingfei Wu, Qingsong Wen*, "RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models," in the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, USA, Oct. 2024. [arXiv]
• [C69] [CIKM'24] Shubao Zhao, Ming Jin, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Qingsong Wen, Yi Wang, "HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting," in the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, USA, Oct. 2024. [arXiv]
• [C68] [CIKM'24] Chaoli Zhang, Yingying Zhang, Lanshu Peng, Qingsong Wen, Yiyuan Yang, Chongjiong Fan, Minqi Jiang, Lunting Fan, Liang Sun, "Advancing Multivariate Time Series Anomaly Detection: A Comprehensive Benchmark with Real-World Data from Alibaba Cloud," in the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, USA, Oct. 2024.
• [C67] [KDD'24] Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen*, "Foundation Models for Time Series Analysis: A Tutorial and Survey", in 30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Barcelona, Spain, Aug. 2024. [arXiv]
• [C66] [KDD'24] Aoxiao Zhong, Dengyao Mo, Guiyang Liu, Jinbu Liu, Qingda Lu, Qi Zhou, Jiesheng Wu, Quanzheng Li, Qingsong Wen, "LogParser-LLM: Advancing Efficient Log Parsing with Large Language Models", in 30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Barcelona, Spain, Aug. 2024. [arXiv]
• [C65] [KDD'24] Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng, "Cluster-Wide Task Slowdown Detection in Cloud Systems", in 30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Barcelona, Spain, Aug. 2024. [arXiv]
• [C64] [KDD'24] Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song, "Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting", in 30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Barcelona, Spain, Aug. 2024. [arXiv] [code]
• [C63] [ICML'24] Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang*, Bin Yang, Jindong Wang, Shirui Pan*, Qingsong Wen*, "Position: What Can Large Language Models Tell Us about Time Series Analysis," in the International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024. [arXiv]
• [C62] [ICML'24] Shikai Fang, Qingsong Wen*, Yingtao Luo, Shandian Zhe, Liang Sun, "BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition, " in the International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024. (ICML Spotlight, Top 3.5%) [arXiv] [code]
• [C61] [ICLR'24] Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan*, Qingsong Wen*, "Time-LLM: Time Series Forecasting by Reprogramming Large Language Models," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C60] [ICLR'24] Hao Cheng, Qingsong Wen*, Yang Liu, Liang Sun, "RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C59] [ICLR'24] Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen*, "Explaining Time Series via Contrastive and Locally Sparse Perturbations," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C58] [ICLR'24] Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin, "CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C57] [ICLR'24] Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo, "Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C56] [ICLR'24] Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei, "EasyTPP: Towards Open Benchmarking Temporal Point Processes," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. [arXiv] [code]
• [C55] [ICLR'24] Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan, "Online GNN Evaluation Under Test-time Graph Distribution Shifts," in the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 2024. (ICLR Spotlight, Top 5%) [arXiv] [code]
• [C54] [WWW'24] Feiyi Chen, Zhen Qin, Mengchu Zhou, Yingying Zhang, Shuiguang Deng, Lunting Fan, Guansong Pang, Qingsong Wen, "LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection," In the ACM Web Conference 2024 (WWW '24), Singapore, May 2024. [arXiv]
• [C53] [WWW'24] Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, Yuxuan Liang, "UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web," In the ACM Web Conference 2024 (WWW '24), Singapore, May 2024. [arXiv]
• [C52] [VLDB'24] Yunyao Cheng, Peng Chen, Chenjuan Guo, Kai Zhao, Qingsong Wen, Bin Yang, Christian S. Jensen, "Weakly Guided Adaptation for Robust Time Series Forecasting," in the 50th International Conference on Very Large Data Bases (VLDB 2024), Guangzhou, China, Aug. 2024. [paper]
• [C51] [ICDE'24] Feiyi Chen, Yingying zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng, "Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection," in IEEE 40th International Conference on Data Engineering (ICDE 2024), Utrecht, Netherlands, May 2024. [arXiv]
• [C50] [IJCAI'24] Huaiwu Zhang, Yutong Xia, Siru Zhong, Kun Wang, Zekun Tong, Qingsong Wen, Roger Zimmermann, Yuxuan Liang, "Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach", in the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2023), Jeju Island, South Korea, Aug. 2024. [arXiv]
• [C49] [SDM'24] Qiang Li, Yiqiao Sun, Linsey Pang, Liang Sun, Qingsong Wen, "Stable Synthetic Control with Anomaly Detection for Causal Inference," in Proc. SIAM International Conference on Data Mining (SDM 2024), Houston, USA, April 2024.
• [C48] [ICASSP'24] Zhiqiang Zhou, Linxiao Yang, Qingsong Wen, Liang Sun, "RobustTSVar: A Robust Time Series Variance Estimation Algorithm," in Proc. IEEE 49th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, April 2024.
• [C47] [ICASSP'24] Kexin Zhang, Qingsong Wen*, Chaoli Zhang, Liang Sun, Yong Liu, "Skip-Step Contrastive Predictive Coding for Time Series Anomaly Detection," in Proc. IEEE 49th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, April 2024.
• [C46] [NeurIPS'23] Yifan Zhang, Qingsong Wen*, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan, "OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling," in Proc. 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, USA, Dec. 2023. [arXiv] [code]
• [C45] [NeurIPS'23] Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao, "ADGym: Design Choices for Deep Anomaly Detection," in Proc. 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, USA, Dec. 2023. (D&B Track) [arXiv] [code]
• [C44] [KDD'23] Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen*, Liang Sun, "DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection", in Proc. 29th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2023), Long Beach, USA, Aug. 2023. (Research Track, Acceptance Rate 313/1416=22.10%) [arXiv] [code]
• [C43] [VLDB'23] Zhicheng Pan, Yihang Wang, Yingying Zhang, Sean Bin Yang, Peng Chen, Yunyao Cheng, Chenjuan Guo, Qingsong Wen, Xiduo Tian, Yunliang Dou, Zhiqiang Zhou, Chengcheng Yang, Aoying Zhou, Bin Yang, "MagicScaler: Uncertainty-aware, Predictive Autoscaling", in the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, Aug. 2023. [paper]
• [C42] [IJCAI'23] Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun, "Transformers in Time Series: A Survey", in the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, China, Aug. 2023. [arXiv] [Website]. Selected by Paper Digest into Most Influential IJCAI Papers (Version: 2023-09), Rank 1st (1/700+ IJCAI'23 papers).
• [C41] [SIGSPATIAL'23] Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang, "DiffSTG: Probabilistic spatio-temporal graph forecasting with denoising diffusion models", In Proc. 31st International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2023), Hamburg, Germany, Nov. 2023. [arXiv] [code]
• [C40] [ICASSP'23] Qingsong Wen, Linxiao Yang, Liang Sun, "Robust Dominant Periodicity Detection for Time Series with Missing Data", in Proc. IEEE 48th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes Island, Greece, June 2023. [arXiv]
• [C39] [ICASSP'23] Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun, "SaDI: A Self-Adaptive Decomposed Interpretable Framework for Electricity Load Forecasting under Extreme Events", in Proc. IEEE 48th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes Island, Greece, June 2023. [arXiv]
• [C38] [AAAI'23] Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann, "AirFormer: Predicting Nationwide Air Quality in China with Transformers", in Proc. of The 37th AAAI Conference on Artificial Intelligence (AAAI 2023), Washington DC, USA, Feb. 2023. [arXiv] [code]
• [C37] [AAAI'23] Zhiqiang Zhou, Chaoli Zhang, Lingna Ma, Jing Gu, Huajie Qian, Qingsong Wen, Liang Sun, Peng Li, Zhimin Tang, "AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes", in Proc. AAAI Conference on Artificial Intelligence and 35th Annual Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI 2023), Washington DC, USA, Feb. 2023. [arXiv] (AAAI/IAAI 2023 Innovative Application Award)
• [C36] [AAAI'23] Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Qingsong Wen, Liang Sun, "eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms", in Proc. AAAI Conference on Artificial Intelligence and 35th Annual Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI 2023), Washington DC, USA, Feb. 2023. [paper] (AAAI/IAAI 2023 Innovative Application Award)
• [C35] [NeurIPS'22] Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin, "FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting", in Proc. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, Dec. 2022. [arXiv] [code] (NeurIPS Oral, Top 2%)
• [C34] [NeurIPS'22] Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan, "Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment," in Proc. 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, Dec. 2022. [arXiv] [code]
• [C33] [ICML'22] Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin, "FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting," in Proc. 39th International Conference on Machine Learning (ICML 2022), Baltimore, USA, July 17-23, 2022. (Acceptance Rate=1117/5630=19.8%) [arXiv] [code]
• [C32] [KDD'22] Weiqi Chen, Wenwei Wang, Bingqing Peng, Qingsong Wen, Tian Zhou, Liang Sun, "Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting", in Proc. 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2022), Washington DC, USA, Aug. 2022. (Research Track, Acceptance Rate 254/1695=14.99%) [paper] [code]
• [C31] [KDD'22] Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun, "Robust Time Series Analysis and Applications: An Industrial Perspective", in Proc. 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2022), Washington DC, USA, Aug. 2022. [paper] [Website]
• [C30] [CIKM'22] Chaoli Zhang, Tian Zhou, Qingsong Wen*, Liang Sun, "TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis," in Proc. 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), Atlanta, USA, Oct. 2022. [arXiv] [paper] [code]
• [C29] [CIKM'22] Xiaomin Song, Qingsong Wen, and Liang Sun, "Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection," in Proc. 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), Atlanta, USA, Oct. 2022. [arXiv]
• [C28] [ICASSP'22] Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun (All authors equally contributed), "NetRCA: An Effective Network Fault Cause Localization Algorithm," in Proc. IEEE 47th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022), Singapore, May 2022. [arXiv] (ICASSP'22 AIOps Challenge, First Place (1/382))
• [C27] [ICDE'22] Huajie Qian, Qingsong Wen, Liang Sun, Jing Gu, Qiulin Niu, Zhimin Tang, "RobustScaler: QoS-Aware Autoscaling for Complex Workloads," in Proc. IEEE 38th International Conference on Data Engineering (ICDE 2022), Kuala Lumpur, Malaysia, May 2022. [arXiv]
• [C26] [IJCAI'21] Qingsong Wen, Liang Sun, Fan Yang, Xiaomin Song, Jingkun Gao, Xue Wang, Huan Xu, "Time Series Data Augmentation for Deep Learning: A Survey," in the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), Montreal, Canada, Aug. 2021. [paper] [arXiv]. Selected by Paper Digest into Most Influential IJCAI Papers (Version: 2022-02), Rank 1st (1/600+ IJCAI'21 papers).
• [C25] [SIGMOD'21] Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu, "RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection," in Proc. ACM SIGMOD International Conference on Management of Data (SIGMOD 2021), Xi'an, China, Jun. 2021. (Research Track) [arXiv]
• [C24] [CIKM'21] Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, Min Ke, "CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms," in Proc. 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), Queensland, Australia, Nov. 2021. (Applied Research Track, Oral, Top 20/290=6.9%) [arXiv]
• [C23] [ICASSP'21] Qingyang Xu, Qingsong Wen, Liang Sun, "Two-Stage Framework for Seasonal Time Series Forecasting," in Proc. IEEE 46th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021), Toronto, Canada, Jun. 2021. [arXiv]
• [C22] [ICASSP'21] Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun, "A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition," in Proc. IEEE 46th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021), Toronto, Canada, Jun. 2021.
• [C21] [KDD'20] Qingsong Wen, Zhe Zhang, Yan Li, Liang Sun, "Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns," in Proc. 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), San Diego, USA, Aug. 2020. (Research Track, Acceptance Rate 216/1279=16.9%) [paper]
• [C20] [ICASSP'20] Qingsong Wen, Zhengzhi Ma, Liang Sun, "On Robust Variance Filtering and Change of Variance Detection," in Proc. IEEE 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, May 2020. [paper]
• [C19] [IJCAI'19] Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Jian Tan, "RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering," in Proc. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, Aug. 2019. (Acceptance Rate 850/4752=17.9%) [arXiv]
• [C18] [AAAI'19] Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu, "RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series," in Proc. 33th AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, Hawaii, USA, Jan. 2019. (Acceptance Rate 1150/7095=16.2%) [arXiv]

Signal Processing, Wireless Communications, and VLSI/FPGA: LLL, Lattice Reduction, MIMO, Peak to Average Power Ratio (PAPR) Reduction, OFDM, B3G/4G/5G, etc.

• [C17] [ICASSP'16] Qingsong Wen and Xiaoli Ma, "Fixed-complexity variants of the effective LLL algorithm with greedy convergence for MIMO detection," in Proc. IEEE 41th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Shanghai, China, Mar. 2016, pp. 3826-3830.
• [C16] [ISCAS'16] Qingsong Wen and Xiaoli Ma, "VLSI implementation of incremental fixed-complexity LLL lattice reduction for MIMO detection," in Proc. IEEE International Symposium on Circuits and Systems (ISCAS 2016), Montreal, Canada, May 2016, pp. 1898-1901.
• [C15] [GLOBECOM'14] Qingsong Wen, Qi Zhou, and Xiaoli Ma, "An enhanced fixed-complexity LLL algorithm for MIMO detection," in Proc. IEEE Global Communications Conference (GLOBECOM 2014), Austin, TX, Dec. 2014, pp. 3231-3236.
• [C14] [MILCOM'14] Qingsong Wen and Xiaoli Ma, "An efficient greedy LLL algorithm for MIMO detection," in Proc. IEEE 33th Military Communications Conference (MILCOM 2014), Baltimore, MD, Oct. 2014, pp. 550-555.
• [C13] [ICASSP'13] Qingsong Wen, Qi Zhou, Chunming Zhao, and Xiaoli Ma, "Fixed-point realization of lattice-reduction aided MIMO receivers with complex K-best algorithm," in Proc. IEEE 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), Vancouver, Canada, May 2013, pp. 5031-5035.
• [C12] [ASILOMAR'12] Qingsong Wen, Sungeun Lee, and Xiaoli Ma, "Clipping effect on radiation pattern in downtilt beamforming," in Proc. IEEE 46th Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2012), Pacific Grove, CA, Nov. 4-7, 2012, pp. 1873-1877.
• [C11] [ASILOMAR'12] Sungeun Lee, Xiaoli Ma, and Qingsong Wen, "Transmitter-side timing adjustment to mitigate interference between multiple nodes for OFDMA mesh network," in Proc. IEEE 46th Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2012), Pacific Grove, CA, Nov. 4-7, 2012, pp. 1957-1961.
• [C10] [NSWCTC'09] Qihui Liang, Qingsong Wen, Yue Xiao, Shaoqian Li, "A comparison of SCR and active-Set methods for PAPR reduction in OFDM systems," in Proc. International Conference on Networks Security, Wireless Communications and Trusted Computing (NSWCTC 2009), Wuhan, China, Apr. 25-26, 2009, pp. 489-495.
• [C9] [VTC'08] Qingsong Wen, Yue Xiao, Peng Cheng, Lilin Dan, Shaoqian Li, "A modified partial transmit sequence scheme for PAPR reduction in OFDM system," in Proc. IEEE 68th Vehicular Technology Conference (VTC 2008), Calgary, Canada, Sept.21-24, 2008, pp. 1-5.
• [C8] [WiCOM'08] Qingsong Wen, Yue Xiao, Peng Cheng, Cong Zhang, Shaoqian Li, "S-PTS for PAPR reduction in OFDM systems," in Proc. IEEE 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2008), Dalian, China, Oct. 12-14, 2008, pp. 1-4.
• [C7] [ICCS'08] Peng Cheng, Qingsong Wen, Haichao Guo, Yue Xiao, Shaoqian Li, "Maximum diversity gain for single-antenna vector OFDM system," in Proc. IEEE 11th International Conference on Communication Systems (ICCS 2008), Guangzhou, China, Nov 19-21, 2008, pp. 1050-1054.
• [C6] [AICT'08] Xu He, Qingsong Wen, Yue Xiao, Shaoqian Li, "A novel method for reducing the side information of MSR-OFDM system," in Proc. Fourth Advanced International Conference on Telecommunications (AICT 2008), Athens, Greece, Jun. 8-13, 2008, pp. 404-407.
• [C5] [ICCCAS'07] Qingsong Wen, Yue Xiao, Shaoqian Li, "LC-APTS for PAPR reduction in OFDM systems," in Proc. IEEE International Conference on Communications, Circuits and Systems (ICCCAS 2007), Kokura, Japan, Jul, 11-13, 2007, pp. 280-283.
• [C4] [AICT'07] Yue Xiao, Qingsong Wen, Xia Lei, Shaoqian Li, "Improved PTS for PAPR reduction in OFDM systems," in Proc. Fourth Advanced International Conference on Telecommunications (AICT 2007), Morne, Mauritius, May 13-19, 2007, pp. 1-4.
• [C3] [VTC'07] Lilin Dan, Qingsong Wen, Yue Xiao and Shaoqian Li, "A novel user grouping scheme for PAPR reduction in MC-CDMA system," in Proc. IEEE 66th Vehicular Technology Conference (VTC 2007), Baltimore, MD, Sep. 30 - Oct. 3, 2007, pp 994-998.
• [C2] [MCWC'06] Sisi Liu, Yue Xiao, Qingsong Wen and Shaoqian Li, "A low complexity code selection method for peak to average power ratio reduction in MC-CDMA," in Proc. International Conference on Mobile Computing and Wireless Communication (MCWC 2006), Amman, Jordan, Sep.17-20, 2006, pp. 139-144.
• [C1] [ICCCAS'06] Qingsong Wen, Yue Xiao, Shaoqian Li, H. Kayama, Chunlin Yan, "The implement of low-PAPR OFDM system," in Proc. IEEE International Conference on Communications, Circuits and Systems (ICCCAS 2006), Guilin, China, Jun. 25-28, 2006, pp. 1226-1229.

• [J34] [CSUR'25] Yiyuan Yang, Ming Jin, Haomin Wen, Chaoli Zhang, Yuxuan Liang, Lintao Ma, Yi Wang, Chenghao Liu, Bin Yang, Zenglin Xu, Shirui Pan*, Qingsong Wen*, "A Survey on Diffusion Models for Time Series and Spatio-Temporal Data," ACM Computing Surveys, 2025. (IF=28) [arXiv]
• [J33] [AI Magazine'25] Tianlong Xu, Yi-Fan Zhang, Zhendong Chu, Qingsong Wen*, "Multimodal AI Teacher: Integrating Edge Computing and Reasoning Models for Enhanced Student Error Analysis," AAAI AI Magazine, 2025. [paper]
• [J32] [SPM'25] Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen*, "Large Language Models for Education: A Survey and Outlook," IEEE Signal Processing Magazine, 2025. [arXiv]
• [J31] [SPM'25] Xinliang Zhou, Chenyu Liu, Zhisheng Chen, Kun Wang, Yi Ding, Ziyu Jia, Qingsong Wen*, "Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery," IEEE Signal Processing Magazine, 2025. [arXiv]
• [J30] [TKDE'25] Zahra Zamanzadeh Darban, Yiyuan Yang, Geoffrey I. Webb, Charu C. Aggarwal, Qingsong Wen, Shirui Pan, Mahsa Salehi, "DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series," IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025. [arXiv]
• [J29] [TPAMI'25] Tianxiang Zhan, Yuanpeng He, Yong Deng, Zhen Li, Wenjie Du, Qingsong Wen, "Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025. [arXiv]
• [J28] [TPAMI'25] Ming Jin, Guangsi Shi, Yuan-Fang Li, Bo Xiong, Tian Zhou, Flora D. Salim, Liang Zhao, Lingfei Wu, Qingsong Wen*, Shirui Pan*, "Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025. [arXiv]
• [J27] [TPAMI'24] Kexin Zhang, Qingsong Wen*, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan, "Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024. [arXiv] [paper] [Website]
• [J26] [TPAMI'24] Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, Cesare Alippi, Geoffrey I. Webb, Irwin King, Shirui Pan, "A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024. [arXiv] [paper] [Website]
• [J25] [IoT-J'24] Gouheng Zhao, Kai Ying, Qingsong Wen, Linshan Zhao, Jian Pang, Pengcheng Jia, Ming Zhou, Lin Gui, "Analysis and Behavioral Modeling Using Augmented Transformer for Satellite Communication Power Amplifiers," IEEE Internet of Things Journal (IoT-J), 2024. [paper]
• [J24] [JPM'24] Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren, "Large Language Models for Financial and Investment Management: Models, Opportunities and Challenges," The Journal of Portfolio Management (JPM), 2024. [paper]
• [J23] [JPM'24] Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren, "Large Language Models for Financial and Investment Management: Applications and Benchmarks," The Journal of Portfolio Management (JPM), 2024. [paper]
• [J22] [KBS'24] Shubao Zhao, Xinxing Zhou, Ming Jinc, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Qingsong Wen, Yi Wang, Yanlong Wen, Xiaojie Yuan, "Rethinking Self-Supervised Learning for TimeSeries Forecasting: A Temporal Perspective," Knowledge-Based Systems (KBS), 2024. [paper]
• [J21] [TKDE'24] Huanyu Zhang, YiFan Zhang, Zhang Zhang, Qingsong Wen, Liang Wang, "LogoRA: Local-Global Representation Alignment for Robust Time Series Classification," IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. [paper] [arXiv]
• [J20] [IS'24] Tianlong Xu, Richard Tong, Jing Liang, Xing Fan, Haoyang Li, Qingsong Wen, "Foundation Models for Education: Promises and Prospects", IEEE Intelligent Systems, 2024. [arXiv] [paper]
• [J19] [TPWRS'24] Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, and Yi Wang, "DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model," IEEE Trainsactions on Power Systems (TPWRS), 2024. [arXiv] [paper]
• [J18] [TSG'24] Dalin Qin, Qingsong Wen, Zhiqiang Zhou, Liang Sun, and Yi Wang, "Deciding When to Use A Personalized Model for Load Forecasting," IEEE Transactions on Smart Grids (TSG), 2024. [paper]
• [J17] [TSG'24] Yangze Zhou, Qingsong Wen, Jie Song, Xueyuan Cui, and Yi Wang, "Load Data Valuation in Multi-Energy Systems: An End-to-End Approach," IEEE Transactions on Smart Grid (TSG), 2024. [paper] [arXiv]
• [J16] [TSG'24] Nan Lu, Shu Liu, Qingsong Wen, Qiming Chen, Liang Sun, Yi Wang, "Federated Domain Separation for Distributed Forecasting of Non-IID Household Loads," IEEE Transactions on Smart Grid (TSG), 2024. [paper]
• [J15] [TSG'23] Dalin Qin, Chenxi Wang, Qingsong Wen, Weiqi Chen, Liang Sun, and Yi Wang, "Personalized Federated DARTS for Electricity Load Forecasting of Individual Buildings," IEEE Transactions on Smart Grid (TSG), 2023. (IF=10.275) [paper]
• [J14] [TSG'23] Chenxi Wang, Yangze Zhou, Qingsong Wen, and Yi Wang, "Improving Load Forecasting Performance via Sample Reweighting," IEEE Transactions on Smart Grid (TSG), 2023. (IF=10.275) [paper]
• [J13] [TSG'23] Miha Grabner, Yi Wang, Qingsong Wen, Boštjan Blažič, Vitomir Štruc, "A Global Modeling Approach for Load Forecasting in Distribution Networks", IEEE Transactions on Smart Grid (TSG), 2023. (IF=10.275) [arXiv] [paper] [code]
• [J12] [AI Magazine'23] Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Xinyue Gu, Jin Wang, Qiming Chen, Linxiao Yang, Qingsong Wen, Liang Sun, "Energy Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms," AAAI AI Magazine, 2023. [paper]
• [J11] [CEP'23] Qiming Chen, Qingsong Wen, Xialai Wu, Xun Lang, Yao Shi, Lei Xie, Hongye Su, "Detection and time–frequency analysis of multiple plant-wide oscillations using adaptive multivariate intrinsic chirp component decomposition," IFAC Control Engineering Practice, 2023. (IF=4.9) [paper]
• [J10] [AAS'23] Qiming Chen, Qingsong Wen, Xun Lang, Lei Xie, Hongye Su, "Univariate and Multivariate Signal Decomposition: Review and Future Directions", in Acta Automatica Sinica (AAS), 2023. (CCF-A) [paper]
• [J9] [RPG'23] Jiahao Ma, Ning Zhang, Qingsong Wen, Yi Wang, "An Efficient Local Multi-Energy Systems Planning Method with Long-term Storage," IET Renewable Power Generation, 2023. (IF=3.034)
• [J8] [APEN'23] Yi Wang, Jiahao Ma, Ning Gao, Qingsong Wen, Liang Sun, and Hongye Guo, "Federated Fuzzy K-means for Privacy-Preserving Behavior Analysis in Smart Grids," Applied Energy (APEN), 2023. (IF=11.446) [paper]
• [J7] [PIEEE'23] Yi Wang, Chien-fei Chen, Peng-Yong Kong, Husheng Li, and Qingsong Wen, "A Cyber-Physical-Social Perspective on Future Smart Distribution Systems," Proceedings of the IEEE (PIEEE), 2023. (IF=20.6) [paper]
• [J6] [TKDE'22] Longyuan Li, Junchi Yan, Qingsong Wen, Yaohui Jin, and Xiaokang Yang, "Learning Robust Deep State Space for Unsupervised Anomaly Detection in Contaminated Time-Series," IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. (IF=9.235) [paper]
• [J5] [iEnergy'22] Chenxi Wang, Dalin Qin, Qingsong Wen, Tian Zhou, Liang Sun, and Yi Wang, "Adaptive Probabilistic Load Forecasting for Individual Buildings," iEnergy, 2022. [paper]
• [J4] [TPWRS'22] Yihong Zhou, Zhaohao Ding, Qingsong Wen, Yi Wang, "Robust Load Forecasting towards Adversarial Attacks via Bayesian Learning," IEEE Transactions on Power Systems (TPWRS), 2022. (IF=7.326) [paper]
• [J3] [TWC'16] Qingsong Wen and Xiaoli Ma, "Efficient Greedy LLL Algorithms for Lattice Decoding," IEEE Transactions on Wireless Communications (TWC 2016), vol. 15, no. 5, pp. 3560-3572, May 2016. (IF=8.346) [paper]
• [J2] [WPC'10] Su Hu, Gang Wu, Qingsong Wen, Yue Xiao, Shaoqian Li, "Nonlinearity Reduction by Tone Reservation with Null Subcarriers for WiMAX System," Springer Wireless Personal Communications (WPC), vol. 54, no. 2, pp. 289-305, 2010. [paper]
• [J1] [SPL'07] Yue Xiao, Xia Lei, Qingsong Wen, Shaoqian Li, "A Class of Low Complexity PTS Techniques for PAPR Reduction in OFDM Systems," IEEE Signal Processing Letters. (SPL), vol. 14, no. 10, Oct. 2007. [paper]

• [B1] Xi Zhu, Yu Wang, Hang Gao, Wujiang Xu, Chen Wang, Zhiwei Liu, Kun Wang, Mingyu Jin, Linsey Pang, Qingsong Weng, Philip S. Yu and Yongfeng Zhang, "Recommender Systems Meet Large Language Model Agents: A Survey", Foundations and Trends® in Privacy and Security, 2025. [link]
• [B2] Min Wu, Eldele Emadeldeen, Zhenghua Chen, Qingsong Wen, Shirui Pan, Xiaoli Li, "AI for Time Series: Unlocking Patterns with Deep Learning", CRC Press, 2025. (in-process)
• [B3] Min Wu, Eldele Emadeldeen, Zhenghua Chen, Qingsong Wen, Shirui Pan, Xiaoli Li, "AI for Time Series: Building Robust and Generalizable Models", CRC Press, 2025. (in-process)

• [BC1] Qingsong Wen, Ren Chen, Yinglong Xia, Li Zhou, Juan Deng, Jian Xu, Mingzhen Xia, "Big-Data Helps SDN to Verify Integrity of Control/Data Planes," in Big-Data and Software Defined Networking, IET Book Series on Big Data, ISBN: 9781785613043, DOI: 10.1049/PBPC015E Mar. 2018. [Invited Book Chapter] [link] [pdf]
• [BC2] Hang Li, Tianlong Xu, Qingsong Wen*, "Leverage LLMs on Knowledge Tagging for Math Questions in Education," in Future of Learning with Large Language Models, CRC Press, 2025.

• [P17] "AI-Based Method for Identifying Error Cause, Apparatus, Device, and Storage Medium", in Patent Application, filed in 2025.
• [P16] "A Hotspot Partition Positioning Scheme based on Comprehensive Index Sorting in NoSQL System", in Patent Application, filed in 2023.
• [P15] "A Time Series Forecasting System with Robustness Against Anomalies", in Patent Application, filed in 2023.
• [P14] "An Efficient Method for Anomaly Detection of Time Series Data Based on Contrastive Representation Learning", in Patent Application, filed in 2023.
• [P13] "A General Robust Multi-Period Detection System for Time Series Data", in Patent Application, filed in 2023.
• [P12] "A Time Series Subsequence Anomaly Detection System Based on Graph Neural Network", in Patent Application, filed in 2023.
• [P11] "A Cloud Resource Automatic Scaling Algorithm Based on Probabilistic Load Forecasting", in Patent Application, filed in 2023.
• [P10] "A Universal Forecasting System for Heterogeneous Power Time Series Based on Automatic Machine Learning", in Patent Application, filed in 2023.
• [P9] "An Effective System for Locating Causes of Network Faults", in Patent Application, filed in 2022.
• [P8] Xiaomin Song, Jingkun Gao, Qingsong Wen, Bo Yang, Kai He, Yan Li, Juan Bian, Liang Sun. "Robust Time Series Anomaly Detection System for Commercial Data," in Patent Application, filed in Jan 2020.
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• [P6] Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun, "Distance Measurement for Time Series," in US Patent Pending, No.: US20220156321A1, 2022 [link]
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• [P2] Xiaoli Ma and Qingsong Wen, "Multi-Input Multi-Output (MIMO) Detection Systems," in US Patent No.: US 9,705,646 B2, Jul. 11, 2017. [link]
• [P1] Lilin Dan, Yue Xiao, Yongrui Peng, Ten Li, Qingsong Wen, Shaoqian Li, Chunlin Yan, Zhan Zhang, and Hidetoshi Kayama, "Method and Device for Processing Multi-carrier Signal," in China Patent No. CN101729475, Japan Patent No. JP2010098734, 2013. [link]

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