Lian, Defu

M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Chen, J., Xiao, S., Zhang, P., Luo, K., Lian, D., & Liu, Z. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingInformation Retrieval and Search Behavior

Cited by 757

C-Pack: Packed Resources For General Chinese Embeddings

Xiao, S., Liu, Z., Zhang, P., Muennighoff, N., Lian, D., & Nie, J.-Y. (2024) · Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Topic ModelingMultimodal Machine Learning Applications

Cited by 523

C-Pack: Packed Resources For General Chinese Embeddings

Xiao, S., Liu, Z., Zhang, P., Muennighoff, N., Lian, D., & Nie, J.-Y. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 514

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

Binarized attributed network embedding

Yang, H., Pan, S., Zhang, P., Chen, L., Lian, D., & Zhang, C. (2018) · 2018 IEEE International Conference on Data Mining (ICDM)

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 102

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Huang, X., Lian, J., Lei, Y., Yao, J., Lian, D., & Xie, X. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 89

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Huang, X., Lian, J., Lei, Y., Yao, J., Lian, D., & Xie, X. (2025) · ACM Transactions on Information Systems

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 89

MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation

Qian, H., Liu, Z., Zhang, P., Mao, K., Lian, D., Dou, Z., & Huang, T. (2025) · Proceedings of the ACM on Web Conference 2025

Topic ModelingInformation Retrieval and Search Behavior

Cited by 86

Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data

Pang, G., Cao, L., Chen, L., Lian, D., & Liu, H. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Anomaly Detection Techniques and ApplicationsAdvanced Statistical Methods and Models

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

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