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Wenpeng Yin
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Research Interests:
Universal Natural Language Processing. Aim at finding common patterns in diverse NLP problems, and building a unified system that can generalize as well as human beings.
Trustworthy Machine Intelligence. Adversarial representation learning, debiasing repre- sentation learning, explainable representation learning, goal-oriented evaluation and universal representation learning.
Universal Natural Language Processing. Aim at finding common patterns in diverse NLP problems, and building a unified system that can generalize as well as human beings.
Trustworthy Machine Intelligence. Adversarial representation learning, debiasing repre- sentation learning, explainable representation learning, goal-oriented evaluation and universal representation learning.
Papers49 papers
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COLING, pp.3436-3440, (2020)
Andre Esteva, Anuprit Kale, Romain Paulus,Kazuma Hashimoto,Wenpeng Yin,Dragomir Radev,Richard Socher
IEEE Transactions on Knowledge and Data Engineering, pp.1-1, (2019)
Cited by5Bibtex
north american chapter of the association for computational linguistics, (2019)
Neural Computing and Applications, pp.1-12, (2019)
EMNLP/IJCNLP (1), pp.3912-3921, (2019)
Cited by2EIBibtex
IEEE Transactions on Affective Computing, pp.1-1, (2019)
Cited by7Bibtex
*SEM@NAACL-HLT, (2018): 203-213
TACL, (2018): 687-702
empirical methods in natural language processing, (2018)
Bibtex
EMNLP, (2018)
COLING, (2018)
meeting of the association for computational linguistics, (2018): 540-545
arXiv preprint arXiv:1702.01923, (2017)
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