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Xiang Lorraine Li
Xiang Lorraine Li
Assistant Professor, University of Pittsburgh
Dirección de correo verificada de pitt.edu - Página principal
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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
6712021
Commonsense knowledge base completion
X Li, A Taheri, L Tu, K Gimpel
Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016
1912016
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
136*2020
Probabilistic embedding of knowledge graphs with box lattice measures
L Vilnis, X Li, S Murty, A McCallum
arXiv preprint arXiv:1805.06627, 2018
1232018
Faith and fate: Limits of transformers on compositionality
N Dziri, X Lu, M Sclar, XL Li, L Jiang, BY Lin, S Welleck, P West, ...
Advances in Neural Information Processing Systems 36, 2024
942024
Smoothing the geometry of probabilistic box embeddings
X Li, L Vilnis, D Zhang, M Boratko, A McCallum
International Conference on Learning Representations, 2018
792018
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
472020
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
40*2021
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
372020
A systematic investigation of commonsense knowledge in large language models
XL Li, A Kuncoro, J Hoffmann, C de Masson d’Autume, P Blunsom, ...
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
36*2022
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
302021
Representing joint hierarchies with box embeddings
D Patel, S Sankar
Automated Knowledge Base Construction, 2020
182020
Improved representation learning for predicting commonsense ontologies
X Li, L Vilnis, A McCallum
arXiv preprint arXiv:1708.00549, 2017
122017
Word2box: Capturing set-theoretic semantics of words using box embeddings
SS Dasgupta, M Boratko, S Mishra, S Atmakuri, D Patel, XL Li, ...
arXiv preprint arXiv:2106.14361, 2021
9*2021
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
92020
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
92016
Editing Commonsense Knowledge in GPT
A Gupta, D Mondal, AK Sheshadri, W Zhao, XL Li, S Wiegreffe, N Tandon
arXiv preprint arXiv:2305.14956, 2023
72023
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
62021
PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning
F Brahman, C Bhagavatula, V Pyatkin, JD Hwang, XL Li, HJ Arai, ...
arXiv preprint arXiv:2305.19472, 2023
52023
Probabilistic Commonsense Knowledge
X Li
2022
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Artículos 1–20