Wen, Qingsong

Transformers in Time Series: A Survey

Wen, Q., Zhou, T., Zhang, C., Chen, W., Ma, Z., Yan, J., & Sun, L. (2023) · Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

Time Series Analysis and ForecastingStock Market Forecasting Methods

Cited by 1,260

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Jin, M., Koh, H. Y., Wen, Q., Zambon, D., Alippi, C., Webb, G. I., King, I., & Pan, S. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Time Series Analysis and ForecastingAdvanced Graph Neural Networks

Cited by 567

DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

Yang, Y., Zhang, C., Zhou, T., Wen, Q., & Sun, L. (2023) · Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Anomaly Detection Techniques and ApplicationsTime Series Analysis and Forecasting

Cited by 387

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Zhang, K., Wen, Q., Zhang, C., Cai, R., Jin, M., Liu, Y., Zhang, J. Y., Liang, Y., Pang, G., Song, D., et al. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Time Series Analysis and ForecastingDomain Adaptation and Few-Shot Learning

Cited by 295

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models

Wen, H., Lin, Y., Xia, Y., Wan, H., Wen, Q., Zimmermann, R., & Liang, Y. (2023) · Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems

Traffic Prediction and Management TechniquesAdvanced Graph Neural Networks

Cited by 130

RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models

Wang, Z., Liu, Z., Zhang, Y., Zhong, A., Wang, J., Yin, F., Fan, L., Wu, L., & Wen, Q. (2024) · Proceedings of the 33rd ACM International Conference on Information and Knowledge Management

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 99

LLM Agents for Education: Advances and Applications

Chu, Z., Wang, S., Xie, J., Zhu, T., Yan, Y., Ye, J., Zhong, A., Hu, X., Liang, J., Yu, P. S., et al. (2025) · Findings of the Association for Computational Linguistics: EMNLP 2025

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 96

Deep Learning for Multivariate Time Series Imputation: A Survey

Wang, J., Du, W., Yang, Y., Qian, L., Cao, W., Zhang, K., Wang, W., Liang, Y., & Wen, Q. (2024) · Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence

Time Series Analysis and ForecastingTraffic Prediction and Management Techniques

Cited by 43

DiffLoad: Uncertainty Quantification in Electrical Load Forecasting With the Diffusion Model

Wang, Z., Wen, Q., Zhang, C., Sun, L., & Wang, Y. (2025) · IEEE Transactions on Power Systems

Energy Load and Power ForecastingSmart Grid Energy Management

Cited by 34

A Survey on Trustworthy LLM Agents: Threats and Countermeasures

Yu, M., Meng, F., Zhou, X., Wang, S., Mao, J., Pang, L., Chen, T., Wang, K., Li, X., Zhang, Y., et al. (2025) · arXiv

Access Control and TrustAdversarial Robustness in Machine Learning

Cited by 34

A Survey on Trustworthy LLM Agents: Threats and Countermeasures

Yu, M., Meng, F., Zhou, X., Wang, S., Mao, J., Pan, L., Chen, T., Wang, K., Li, X., Zhang, Y., et al. (2025) · Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2

Access Control and TrustAdversarial Robustness in Machine Learning

Cited by 34

AutoSurvey: Large Language Models Can Automatically Write Surveys

Wang, Y., Guo, Q., Yao, W., Zhang, H., Zhang, X., Wu, Z., Zhang, M., Dai, X., Zhang, M., Wen, Q., et al. (2024) · arXiv

Survey Methodology and NonresponseTopic Modeling

Cited by 24

AutoSurvey: Large Language Models Can Automatically Write Surveys

Wang, Y., Guo, Q., Yao, W., Zhang, H., Zhang, X., Wu, Z., Zhang, M., Dai, X., Zhang, M., Wen, Q., et al. (2024) · Advances in Neural Information Processing Systems 37

Survey Methodology and NonresponseTopic Modeling

Cited by 24

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

Tie, G., Yuan, Z., Zhao, Z., Hu, C., Gu, T., Zhang, R., Zhang, S., Wu, J., Tu, X., Jin, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16

AI Agent for Information Retrieval: Generating and Ranking

Zhang, Y., Liu, Z., Wen, Q., Pang, L., Liu, W., & Yu, P. S. (2024) · Proceedings of the 33rd ACM International Conference on Information and Knowledge Management

Information Retrieval and Search BehaviorTopic Modeling

Cited by 11

Developing and Deploying Industry Standards for Artificial Intelligence in Education (AIED): Challenges, Strategies, and Future Directions

Tong, R., Li, H., Liang, J., & Wen, Q. (2024) · arXiv

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 5