Liu, Tie-Yan

Learning to rank: from pairwise approach to listwise approach

Cao, Z., Qin, T., Liu, T.-Y., Tsai, M.-F., & Li, H. (2007) · Proceedings of the 24th international conference on Machine learning

Information Retrieval and Search BehaviorRecommender Systems and Techniques

Cited by 1,960

Scientific discovery in the age of artificial intelligence.

Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., et al. (2023) · Nature

Artificial Intelligence ApplicationsMachine Learning in Materials Science

Cited by 1,823

BioGPT: generative pre-trained transformer for biomedical text generation and mining

Luo, R., Sun, L., Xia, Y., Qin, T., Zhang, S., Poon, H., & Liu, T.-Y. (2022) · Briefings in Bioinformatics

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 1,150

A Theoretical Analysis of NDCG Type Ranking Measures

Wang, Y., Wang, L., Li, Y., He, D., Liu, T.-Y., & Chen, W. (2013) · arXiv

Information Retrieval and Search BehaviorRecommender Systems and Techniques

Cited by 351

Incorporating BERT into Neural Machine Translation

Zhu, J., Xia, Y., Wu, L., He, D., Qin, T., Zhou, W., Li, H., & Liu, T.-Y. (2020) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 228

A survey on neural speech synthesis

Tan, X., Qin, T., Soong, F., & Liu, T.-Y. (2021) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 216

On the depth of deep neural networks: a theoretical view

Sun, S., Chen, W., Wang, L., Liu, X., & Liu, T.-Y. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 147

Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Chen, C., Zhao, L., Bian, J., Xing, C., & Liu, T.-Y. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Stock Market Forecasting MethodsFinancial Markets and Investment Strategies

Cited by 73

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

Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder

Lu, S., He, D., Xiong, C., Ke, G., Malik, W., Dou, Z., Bennett, P., Liu, T.-Y., & Overwijk, A. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingInformation Retrieval and Search Behavior

Cited by 49

Breaking the barriers of data scarcity in drug–target affinity prediction

Pei, Q., Wu, L., Zhu, J., Xia, Y., Xie, S., Qin, T., Liu, H., Liu, T.-Y., & Yan, R. (2023) · Briefings in Bioinformatics

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 36

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