Следене
Tianlu Wang
Tianlu Wang
Facebook AI Research
Потвърден имейл адрес: fb.com - Начална страница
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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
16022022
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
10352017
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
8052018
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
4122019
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
3822019
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
2712021
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
1052023
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
832021
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
822020
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
712021
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
702023
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
66*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
622022
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
552022
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
49*2020
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, 2023
482023
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
432016
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
252023
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
202023
Selective annotation makes language models better few-shot learners
SU Hongjin, J Kasai, CH Wu, W Shi, T Wang, J Xin, R Zhang, M Ostendorf, ...
The Eleventh International Conference on Learning Representations, 2022
152022
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