| 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 | 821 | 2017 |
| Gender bias in coreference resolution: Evaluation and debiasing methods J Zhao, T Wang, M Yatskar, V Ordonez, KW Chang Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods, 15–20, 2018 | 577 | 2018 |
| Opt: Open pre-trained transformer language models S Zhang, S Roller, N Goyal, M Artetxe, M Chen, S Chen, C Dewan, ... arXiv preprint arXiv:2205.01068, 2022 | 397 | 2022 |
| 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 | 304 | 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 | 294 | 2019 |
| General multi-label image classification with transformers J Lanchantin, T Wang, V Ordonez, Y Qi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 135 | 2021 |
| 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 | 57 | 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 HLT-NAACL, 249-259, 2016 | 42 | 2016 |
| 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 | 38* | 2020 |
| Selective annotation makes language models better few-shot learners H Su, J Kasai, CH Wu, W Shi, T Wang, J Xin, R Zhang, M Ostendorf, ... The Eleventh International Conference on Learning Representations, 2023 | 33 | 2023 |
| Jingfei Du, et al. 2021. Few-shot learning with multilingual language models XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ... arXiv preprint arXiv:2112.10668, 0 | 27 | |
| Visual news: Benchmark and challenges in news image captioning F Liu, Y Wang, T Wang, V Ordonez Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 26 | 2021 |
| 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 | 18* | 2022 |
| 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 | 15 | 2022 |
| OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization S Iyer, XV Lin, R Pasunuru, T Mihaylov, D Simig, P Yu, K Shuster, T Wang, ... arXiv preprint arXiv:2212.12017, 2022 | 11 | 2022 |
| Feedback-prop: Convolutional neural network inference under partial evidence T Wang, K Yamaguchi, V Ordonez Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 10 | 2018 |
| ALERT: Adapting Language Models to Reasoning Tasks P Yu, T Wang, O Golovneva, B Alkhamissy, G Ghosh, M Diab, ... arXiv preprint arXiv:2212.08286, 2022 | 5 | 2022 |
| Tao Yu H Su, J Kasai, CH Wu, W Shi, T Wang, J Xin, R Zhang, M Ostendorf, ... Selective annotation makes language models better few-shot learners. arXiv …, 2022 | 3 | 2022 |
| Text Characterization Toolkit (TCT) D Simig, T Wang, V Dankers, P Henderson, K Batsuren, D Hupkes, ... Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the …, 2022 | 1 | 2022 |
| Gender Biases in Automatic Evaluation Metrics: A Case Study on Image Captioning H Qiu, ZY Dou, T Wang, A Celikyilmaz, N Peng arXiv preprint arXiv:2305.14711, 2023 | | 2023 |
Vicente OrdóñezAssociate Professor, Computer Science, Rice UniversityVerified email at rice.edu
