Li, Xiang Lorraine

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., Aslanides, J., Henderson, S., Ring, R., Young, S., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 235

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Xiong, W., Li, X. L., Iyer, S., Du, J., Lewis, P., Wang, W. Y., Mehdad, Y., Yih, W.-T., Riedel, S., Kiela, D., et al. (2020) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 112

Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning

Chen, X., Boratko, M., Chen, M., Dasgupta, S. S., Li, X. L., & McCallum, A. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Advanced Graph Neural NetworksTopic Modeling

Cited by 47

Looking Beyond Sentence-Level Natural Language Inference for Question Answering and Text Summarization

Mishra, A., Patel, D., Vijayakumar, A., Li, X. L., Kapanipathi, P., & Talamadupula, K. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 39

Improving Local Identifiability in Probabilistic Box Embeddings

Dasgupta, S. S., Boratko, M., Zhang, D., Vilnis, L., Li, X. L., & McCallum, A. (2020) · arXiv

Bayesian Modeling and Causal InferenceMachine Learning and Data Classification

Cited by 33

Box-To-Box Transformations for Modeling Joint Hierarchies

Dasgupta, S. S., Li, X. L., Boratko, M., Zhang, D., & McCallum, A. (2021) · Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021)

Advanced Graph Neural NetworksTopic Modeling

Cited by 2