Xiang Lorraine Li
Xiang Lorraine Li
Other namesXiang Li
Young Investigator, Allen AI
Verified email at - Homepage
Cited by
Cited by
Scaling language models: Methods, analysis & insights from training gopher
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
Commonsense knowledge base completion
X Li, A Taheri, L Tu, K Gimpel
Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016
Answering complex open-domain questions with multi-hop dense retrieval
W Xiong, XL Li, S Iyer, J Du, P Lewis, WY Wang, Y Mehdad, W Yih, ...
arXiv preprint arXiv:2009.12756, 2020
Probabilistic embedding of knowledge graphs with box lattice measures
L Vilnis, X Li, S Murty, A McCallum
arXiv preprint arXiv:1805.06627, 2018
Smoothing the geometry of probabilistic box embeddings
X Li, L Vilnis, D Zhang, M Boratko, A McCallum
International Conference on Learning Representations, 2019
ProtoQA: A question answering dataset for prototypical common-sense reasoning
M Boratko, XL Li, R Das, T O'Gorman, D Le, A McCallum
arXiv preprint arXiv:2005.00771, 2020
Improving local identifiability in probabilistic box embeddings
S Dasgupta, M Boratko, D Zhang, L Vilnis, X Li, A McCallum
Advances in Neural Information Processing Systems 33, 182-192, 2020
Representing joint hierarchies with box embeddings
D Patel, S Sankar
Automated Knowledge Base Construction, 2020
Looking beyond sentence-level natural language inference for question answering and text summarization
A Mishra, D Patel, A Vijayakumar, XL Li, P Kapanipathi, K Talamadupula
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
Probabilistic box embeddings for uncertain knowledge graph reasoning
X Chen, M Boratko, M Chen, SS Dasgupta, XL Li, A McCallum
arXiv preprint arXiv:2104.04597, 2021
Improved representation learning for predicting commonsense ontologies
X Li, L Vilnis, A McCallum
arXiv preprint arXiv:1708.00549, 2017
Interactive provenance summaries for reproducible science
X Li, X Xu, T Malik
2016 IEEE 12th International Conference on e-Science (e-Science), 355-360, 2016
Reading comprehension as natural language inference: a semantic analysis
A Mishra, D Patel, A Vijayakumar, X Li, P Kapanipathi, K Talamadupula
arXiv preprint arXiv:2010.01713, 2020
A Systematic Investigation of Commonsense Understanding in Large Language Models
XL Li, A Kuncoro, J Hoffmann, CM d'Autume, P Blunsom, A Nematzadeh
EMNLP 2022, 2022
Box-to-box transformations for modeling joint hierarchies
SS Dasgupta, XL Li, M Boratko, D Zhang, A McCallum
Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021
Word2box: Learning word representation using box embeddings
SS Dasgupta, M Boratko, S Atmakuri, XL Li, D Patel, A McCallum
arXiv preprint arXiv:2106.14361, 2021
Probabilistic Commonsense Knowledge
X Li
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