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Mark Yatskar
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Visualbert: A simple and performant baseline for vision and language
LH Li, M Yatskar, D Yin, CJ Hsieh, KW Chang
arXiv preprint arXiv:1908.03557, 2019
18802019
Men also like shopping: Reducing gender bias amplification using corpus-level constraints
J Zhao, T Wang, M Yatskar, V Ordonez, KW Chang
arXiv preprint arXiv:1707.09457, 2017
11452017
Neural motifs: Scene graph parsing with global context
R Zellers, M Yatskar, S Thomson, Y Choi
Proceedings of the IEEE conference on computer vision and pattern …, 2018
10812018
Gender bias in coreference resolution: Evaluation and debiasing methods
J Zhao, T Wang, M Yatskar, V Ordonez, KW Chang
arXiv preprint arXiv:1804.06876, 2018
9592018
QuAC: Question answering in context
E Choi, H He, M Iyyer, M Yatskar, W Yih, Y Choi, P Liang, L Zettlemoyer
arXiv preprint arXiv:1808.07036, 2018
9262018
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
4862019
Don't take the easy way out: Ensemble based methods for avoiding known dataset biases
C Clark, M Yatskar, L Zettlemoyer
arXiv preprint arXiv:1909.03683, 2019
4852019
Gender bias in contextualized word embeddings
J Zhao, T Wang, M Yatskar, R Cotterell, V Ordonez, KW Chang
arXiv preprint arXiv:1904.03310, 2019
4372019
Neural amr: Sequence-to-sequence models for parsing and generation
I Konstas, S Iyer, M Yatskar, Y Choi, L Zettlemoyer
arXiv preprint arXiv:1704.08381, 2017
3592017
Situation Recognition: Visual Semantic Role Labeling for Image Understanding
M Yatskar, L Zettlemoyer, A Farhadi
Conference on Computer Vision and Pattern Recognition, 2016
2962016
Robothor: An open simulation-to-real embodied ai platform
M Deitke, W Han, A Herrasti, A Kembhavi, E Kolve, R Mottaghi, J Salvador, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
2442020
For the sake of simplicity: Unsupervised extraction of lexical simplifications from Wikipedia
M Yatskar, B Pang, C Danescu-Niculescu-Mizil, L Lee
arXiv preprint arXiv:1008.1986, 2010
2162010
What does BERT with vision look at?
LH Li, M Yatskar, D Yin, CJ Hsieh, KW Chang
Proceedings of the 58th annual meeting of the association for computational …, 2020
1532020
Language in a bottle: Language model guided concept bottlenecks for interpretable image classification
Y Yang, A Panagopoulou, S Zhou, D Jin, C Callison-Burch, M Yatskar
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
1462023
A qualitative comparison of CoQA, SQuAD 2.0 and QuAC
M Yatskar
arXiv preprint arXiv:1809.10735, 2018
1122018
Grounded situation recognition
S Pratt, M Yatskar, L Weihs, A Farhadi, A Kembhavi
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
972020
Stating the obvious: Extracting visual common sense knowledge
M Yatskar, V Ordonez, A Farhadi
Proceedings of the 2016 Conference of the North American Chapter of the …, 2016
692016
Visual semantic role labeling for video understanding
A Sadhu, T Gupta, M Yatskar, R Nevatia, A Kembhavi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
672021
See No Evil, Say No Evil: Description Generation from Densely Labeled Images
M Yatskar, M Galley, L Vanderwende, L Zettlemoyer
Lexical and Computational Semantics (* SEM 2014), 110, 2014
632014
Visualbert: A simple and performant baseline for vision and language. arXiv 2019
LH Li, M Yatskar, D Yin, CJ Hsieh, KW Chang
arXiv preprint arXiv:1908.03557 2, 0
62
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