| 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 | 2484 | 2022 |
| 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 | 1193 | 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 | 1023 | 2018 |
| 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 | 511 | 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 | 463 | 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 | 339 | 2021 |
| 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 | 164 | 2023 |
| Opt: Open pre-trained transformer language models, 2022 S Zhang, S Roller, N Goyal, M Artetxe, M Chen, S Chen, C Dewan, ... URL https://arxiv. org/abs/2205.01068 3, 19-0, 2023 | 126 | 2023 |
| 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 | 114 | 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 | 108* | 2022 |
| Scaling autoregressive multi-modal models: Pretraining and instruction tuning L Yu, B Shi, R Pasunuru, B Muller, O Golovneva, T Wang, A Babu, B Tang, ... arXiv preprint arXiv:2309.02591 2 (3), 2023 | 107 | 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, 35-40, 2021 | 98 | 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 | 94 | 2020 |
| 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 | 91 | 2022 |
| Chameleon: Mixed-modal early-fusion foundation models C Team arXiv preprint arXiv:2405.09818, 2024 | 74 | 2024 |
| 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 | 71 | 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 | 61* | 2020 |
| 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 | 49 | 2023 |
| 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 |
| 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 | 38 | 2023 |
Vicente OrdóñezAssociate Professor, Computer Science, Rice Universityrice.edu의 이메일 확인됨