Tao Li

Affiliations:
  • University of Utah, UT, USA


According to our database1, Tao Li authored at least 13 papers between 2016 and 2023.

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Bibliography

2023
Learning Semantic Role Labeling from Compatible Label Sequences.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Neural Learning with Logic for Data Efficiency.
PhD thesis, 2022

PYLON: A PyTorch Framework for Learning with Constraints.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
UnQovering Stereotyping Biases via Underspecified Questions.
CoRR, 2020

UNQOVERing Stereotypical Biases via Underspecified Questions.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Structured Tuning for Semantic Role Labeling.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

On Measuring and Mitigating Biased Inferences of Word Embeddings.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models.
IEEE Trans. Vis. Comput. Graph., 2019

A Logic-Driven Framework for Consistency of Neural Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Augmenting Neural Networks with First-order Logic.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018

2016
Exploiting Sentence Similarities for Better Alignments.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016


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