Yulia Tsvetkov 个人学术档案

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Chris DyerDeepMind, Carnegie Mellon在 google.com 的电子邮件经过验证
Alan W BlackProfessor, Language Technologies Institute, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Vidhisha BalachandranMicrosoft Research, Redmond在 microsoft.com 的电子邮件经过验证
Sachin KumarAllen Institute for AI在 allenai.org 的电子邮件经过验证
Anjalie FieldAssistant Professor, Johns Hopkins University在 jhu.edu 的电子邮件经过验证
Manaal FaruquiResearch Scientist, Google在 google.com 的电子邮件经过验证
Xiaochuang HanUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Shangbin FengUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Yejin ChoiUniversity of Washington / Allen Institute for Artificial Intelligence在 cs.washington.edu 的电子邮件经过验证
Chan Young ParkCarnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Shuly WintnerUniversity of Haifa, Department of Computer Science在 cs.haifa.ac.il 的电子邮件经过验证
Noah A. SmithUniversity of Washington; Allen Institute for Artificial Intelligence在 cs.washington.edu 的电子邮件经过验证
Tianxing HeUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Dan JurafskyProfessor of Linguistics and Computer Science, Stanford University在 stanford.edu 的电子邮件经过验证
Graham NeubigCarnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Zirui WangResearch Scientist, Apple AI/ML在 apple.com 的电子邮件经过验证
David MortensenCarnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
David JurgensAssociate Professor, School of Information and Dept. of Computer Science, University of Michigan在 umich.edu 的电子邮件经过验证
Wang LingGoogle Deepmind在 cs.cmu.edu 的电子邮件经过验证
Waleed AmmarGoogle在 google.com 的电子邮件经过验证

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Yulia Tsvetkov

University of Washington

在 cs.washington.edu 的电子邮件经过验证 - 首页

Natural Language Processing


标题按引用次数排序按年份排序按标题排序	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	695	2021
Style transfer through back-translation S Prabhumoye, Y Tsvetkov, R Salakhutdinov, AW Black ACL 2018, 2018	464	2018
Measuring bias in contextualized word representations K Kurita, N Vyas, A Pareek, AW Black, Y Tsvetkov arXiv preprint arXiv:1906.07337, 2019	433	2019
Problems with evaluation of word embeddings using word similarity tasks M Faruqui, Y Tsvetkov, P Rastogi, C Dyer RepEval 2016, 2016	376	2016
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	349	2019
Massively multilingual word embeddings W Ammar, G Mulcaire, Y Tsvetkov, G Lample, C Dyer, NA Smith arXiv preprint arXiv:1602.01925, 2016	331	2016
Metaphor Detection with Cross-Lingual Model Transfer Y Tsvetkov, L Boytsov, A Gershman, E Nyberg, C Dyer ACL 2014, 248--258, 2014	298	2014
Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics A Pagnoni, V Balachandran, Y Tsvetkov arXiv preprint arXiv:2104.13346, 2021	239	2021
Sparse Overcomplete Word Vector Representations M Faruqui, Y Tsvetkov, D Yogatama, C Dyer, NA Smith ACL 2015, 2015	222	2015
Evaluation of Word Vector Representations by Subspace Alignment Y Tsvetkov, M Faruqui, W Ling, G Lample, C Dyer EMNLP 2015, 2015	192	2015
Explaining black box predictions and unveiling data artifacts through influence functions X Han, BC Wallace, Y Tsvetkov arXiv preprint arXiv:2005.06676, 2020	176	2020
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	171*	2021
Not all contexts are created equal: Better word representations with variable attention W Ling, L Chu-Cheng, Y Tsvetkov, S Amir EMNLP 2015, 2015	165	2015
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	155	2020
Morphological inflection generation using character sequence to sequence learning M Faruqui, Y Tsvetkov, G Neubig, C Dyer NAACL 2016, 2015	152	2015
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	140	2019
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	139	2018
On negative interference in multilingual models: Findings and a meta-learning treatment Z Wang, ZC Lipton, Y Tsvetkov arXiv preprint arXiv:2010.03017, 2020	114	2020
A survey of race, racism, and anti-racism in NLP A Field, SL Blodgett, Z Waseem, Y Tsvetkov arXiv preprint arXiv:2106.11410, 2021	109	2021
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	102	2023

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