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Yulia Tsvetkov
Yulia Tsvetkov
University of Washington
在 cs.washington.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Simvlm: Simple visual language model pretraining with weak supervision
Z Wang, J Yu, AW Yu, Z Dai, Y Tsvetkov, Y Cao
arXiv preprint arXiv:2108.10904, 2021
8312021
Measuring bias in contextualized word representations
K Kurita, N Vyas, A Pareek, AW Black, Y Tsvetkov
arXiv preprint arXiv:1906.07337, 2019
5102019
Style transfer through back-translation
S Prabhumoye, Y Tsvetkov, R Salakhutdinov, AW Black
ACL 2018, 2018
4862018
Problems with evaluation of word embeddings using word similarity tasks
M Faruqui, Y Tsvetkov, P Rastogi, C Dyer
RepEval 2016, 2016
3932016
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings
T Manzini, YC Lim, Y Tsvetkov, AW Black
NAACL 2019, 2019
3822019
Massively multilingual word embeddings
W Ammar, G Mulcaire, Y Tsvetkov, G Lample, C Dyer, NA Smith
arXiv preprint arXiv:1602.01925, 2016
3442016
Metaphor Detection with Cross-Lingual Model Transfer
Y Tsvetkov, L Boytsov, A Gershman, E Nyberg, C Dyer
ACL 2014, 248--258, 2014
3092014
Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
A Pagnoni, V Balachandran, Y Tsvetkov
arXiv preprint arXiv:2104.13346, 2021
2942021
Sparse Overcomplete Word Vector Representations
M Faruqui, Y Tsvetkov, D Yogatama, C Dyer, NA Smith
ACL 2015, 2015
2372015
Can machines learn morality? the delphi experiment
L Jiang, JD Hwang, C Bhagavatula, RL Bras, J Liang, J Dodge, ...
arXiv preprint arXiv:2110.07574, 2021
218*2021
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
M Sclar, Y Choi, Y Tsvetkov, A Suhr
arXiv preprint arXiv:2310.11324, 2023
2052023
Evaluation of Word Vector Representations by Subspace Alignment
Y Tsvetkov, M Faruqui, W Ling, G Lample, C Dyer
EMNLP 2015, 2015
2002015
From pretraining data to language models to downstream tasks: Tracking the trails of political biases leading to unfair NLP models
S Feng, CY Park, Y Liu, Y Tsvetkov
arXiv preprint arXiv:2305.08283, 2023
1962023
Explaining black box predictions and unveiling data artifacts through influence functions
X Han, BC Wallace, Y Tsvetkov
arXiv preprint arXiv:2005.06676, 2020
1902020
Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models
Z Wang, Y Tsvetkov, O Firat, Y Cao
arXiv preprint arXiv:2010.05874, 2020
1892020
Not all contexts are created equal: Better word representations with variable attention
W Ling, L Chu-Cheng, Y Tsvetkov, S Amir
EMNLP 2015, 2015
1682015
Morphological inflection generation using character sequence to sequence learning
M Faruqui, Y Tsvetkov, G Neubig, C Dyer
NAACL 2016, 2015
1562015
Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies
A Field, D Kliger, S Wintner, J Pan, D Jurafsky, Y Tsvetkov
EMNLP 2018, 2018
1552018
Finding microaggressions in the wild: A case for locating elusive phenomena in social media posts
L Breitfeller, E Ahn, D Jurgens, Y Tsvetkov
Proceedings of the 2019 conference on empirical methods in natural language …, 2019
1522019
On negative interference in multilingual models: Findings and a meta-learning treatment
Z Wang, ZC Lipton, Y Tsvetkov
arXiv preprint arXiv:2010.03017, 2020
1352020
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