Chen, Enhong

A survey on multimodal large language models

Yin, S., Fu, C., Zhao, S., Li, K., Sun, X., Xu, T., & Chen, E. (2024) · National Science Review

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 893

A Survey on Large Language Models for Recommendation

Wu, L., Zheng, Z., Qiu, Z., Wang, H., Gu, H., Shen, T., Qin, C., Zhu, C., Zhu, H., Liu, Q., et al. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 515

A survey on large language models for recommendation

Wu, L., Zheng, Z., Qiu, Z., Wang, H., Gu, H., Shen, T., Qin, C., Zhu, C., Zhu, H., Liu, Q., et al. (2024) · World Wide Web

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 515

When large language models meet personalization: perspectives of challenges and opportunities

Chen, J., Liu, Z., Huang, X., Wu, C., Liu, Q., Jiang, G., Pu, Y., Lei, Y., Chen, X., Wang, X., et al. (2024) · World Wide Web

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 367

Large language models for generative information extraction: a survey

Xu, D., Chen, W., Peng, W., Zhang, C., Xu, T., Zhao, X., Wu, X., Zheng, Y., Wang, Y., & Chen, E. (2024) · Frontiers of Computer Science

Topic ModelingNatural Language Processing Techniques

Cited by 326

Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Fu, C., Dai, Y., Luo, Y., Li, L., Ren, S., Zhang, R., Wang, Z., Zhou, C., Shen, Y., Zhang, M., et al. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 291

Mining Mobile User Preferences for Personalized Context-Aware Recommendation

Zhu, H., Chen, E., Xiong, H., Yu, K., Cao, H., & Tian, J. (2015) · ACM Transactions on Intelligent Systems and Technology

Recommender Systems and TechniquesHuman Mobility and Location-Based Analysis

Cited by 157

Lightspeech: Lightweight and Fast Text to Speech with Neural Architecture Search

Luo, R., Tan, X., Wang, R., Qin, T., Li, J., Zhao, S., Chen, E., & Liu, T.-Y. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 67

Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction

Hou, M., Xu, C., Li, Z., Liu, Y., Liu, W., Chen, E., & Bian, J. (2022) · Proceedings of the ACM Web Conference 2022

Time Series Analysis and ForecastingForecasting Techniques and Applications

Cited by 59

Understanding the planning of LLM agents: A survey

Huang, X., Liu, W., Chen, X., Wang, X., Wang, H., Lian, D., Wang, Y., Tang, R., & Chen, E. (2024) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 47

Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion

Hou, M., Xu, C., Liu, Y., Liu, W., Bian, J., Wu, L., Li, Z., Chen, E., & Liu, T.-Y. (2021) · Proceedings of the 30th ACM International Conference on Information & Knowledge Management

Stock Market Forecasting MethodsFinancial Markets and Investment Strategies

Cited by 35

Towards Automatic Discovering of Deep Hybrid Network Architecture for Sequential Recommendation

Cheng, M., Liu, Z., Liu, Q., Ge, S., & Chen, E. (2022) · Proceedings of the ACM Web Conference 2022

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 26

Membership Inference Attacks Against Sequential Recommender Systems

Zhu, Z., Wu, C., Fan, R., Lian, D., & Chen, E. (2023) · Proceedings of the ACM Web Conference 2023

Privacy-Preserving Technologies in DataRecommender Systems and Techniques

Cited by 24

Predicting the Spatio-Temporal Evolution of Chronic Diseases in Population with Human Mobility Data

Wang, Y., Zhou, X., Noulas, A., Mascolo, C., Xie, X., & Chen, E. (2018) · Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

Human Mobility and Location-Based AnalysisData-Driven Disease Surveillance

Cited by 22

Position: AI Evaluation Should Learn from How We Test Humans

Zhuang, Y., Liu, Q., Pardos, Z. A., Kyllonen, P. C., Zu, J., Huang, Z., Wang, S., & Chen, E. (2023) · arXiv

Psychometric Methodologies and TestingIntelligent Tutoring Systems and Adaptive Learning

Cited by 16

Survey of Computerized Adaptive Testing: A Machine Learning Perspective

Zhuang, Y., Liu, Q., Bi, H., Huang, Z., Huang, W., Li, J., Yu, J., Liu, Z., Hu, Z., Hong, Y., et al. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Psychometric Methodologies and TestingIntelligent Tutoring Systems and Adaptive Learning

Cited by 9

Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation

Lyu, Y., Niu, Z., Xie, Z., Zhang, C., Xu, T., Wang, Y., & Chen, E. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 8