Tao Li
Titel
Zitiert von
Zitiert von
Jahr
Augmenting Neural Networks with First-order Logic
T Li, V Srikumar
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
182019
Nlize: A perturbation-driven visual interrogation tool for analyzing and interpreting natural language inference models
S Liu, Z Li, T Li, V Srikumar, V Pascucci, PT Bremer
IEEE transactions on visualization and computer graphics 25 (1), 651-660, 2018
132018
Visual interrogation of attention-based models for natural language inference and machine comprehension
S Liu, T Li, Z Li, V Srikumar, V Pascucci, PT Bremer
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2018
112018
A Logic-Driven Framework for Consistency of Neural Models
T Li, V Gupta, M Mehta, V Srikumar
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
82019
On Measuring and Mitigating Biased Inferences of Word Embeddings
S Dev, T Li, J Philips, V Srikumar
Arxiv, 2019
52019
Exploiting Sentence Similarities for Better Alignments
T Li, V Srikumar
Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016
32016
UNQOVERing Stereotyping Biases via Underspecified Questions
T Li, D Khashabi, T Khot, A Sabharwal, V Srikumar
arXiv preprint arXiv:2010.02428, 2020
2020
On Data Augmentation for Extreme Multi-label Classification
D Zhang, T Li, H Zhang, B Yin
https://arxiv.org/abs/2009.10778, 2020
2020
OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings
S Dev, T Li, JM Phillips, V Srikumar
arXiv preprint arXiv:2007.00049, 2020
2020
Structured Tuning for Semantic Role Labeling
T Li, Jawale, P Anand, M Palmer, V Srikumar
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
2020
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