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Men also like shopping: Reducing gender bias amplification using corpus-level constraints J Zhao, T Wang, M Yatskar, V Ordonez, KW Chang Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 1125 | 2017 |
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Balanced datasets are not enough: Estimating and mitigating gender bias in deep image representations T Wang, J Zhao, M Yatskar, KW Chang, V Ordonez Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 480 | 2019 |
Gender bias in contextualized word embeddings J Zhao, T Wang, M Yatskar, R Cotterell, V Ordonez, KW Chang Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 426 | 2019 |
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Cat-gen: Improving robustness in nlp models via controlled adversarial text generation T Wang, X Wang, Y Qin, B Packer, K Li, J Chen, A Beutel, E Chi Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 93 | 2020 |
Few-shot learning with multilingual generative language models XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 92* | 2022 |
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Identifying and mitigating spurious correlations for improving robustness in nlp models T Wang, R Sridhar, D Yang, X Wang Findings of the Association for Computational Linguistics: NAACL 2022, 2022 | 61 | 2022 |
Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation T Wang, XV Lin, NF Rajani, B McCann, V Ordonez, C Xiong Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 53* | 2020 |
Name tagging for low-resource incident languages based on expectation-driven learning B Zhang, X Pan, T Wang, A Vaswani, H Ji, K Knight, D Marcu Proceedings of the 2016 conference of the North American chapter of the …, 2016 | 45 | 2016 |
Shepherd: A critic for language model generation T Wang, P Yu, XE Tan, S O'Brien, R Pasunuru, J Dwivedi-Yu, ... arXiv preprint arXiv:2308.04592, 2023 | 37 | 2023 |
Understanding in-context learning via supportive pretraining data X Han, D Simig, T Mihaylov, Y Tsvetkov, A Celikyilmaz, T Wang arXiv preprint arXiv:2306.15091, 2023 | 30 | 2023 |
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