Ellie Pavlick
Ellie Pavlick
Verified email at brown.edu - Homepage
Cited by
Cited by
BERT rediscovers the classical NLP pipeline
I Tenney, D Das, E Pavlick
arXiv preprint arXiv:1905.05950, 2019
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
RT McCoy, E Pavlick, T Linzen
arXiv preprint arXiv:1902.01007, 2019
What do you learn from context? probing for sentence structure in contextualized word representations
I Tenney, P Xia, B Chen, A Wang, A Poliak, RT McCoy, N Kim, ...
arXiv preprint arXiv:1905.06316, 2019
Optimizing statistical machine translation for text simplification
W Xu, C Napoles, E Pavlick, Q Chen, C Callison-Burch
Transactions of the Association for Computational Linguistics 4, 401-415, 2016
PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification
E Pavlick, J Ganitkevitch, P Rastogi, B Van Durme, C Callison-Burch
Volume 2: Short Papers, 425, 2015
An empirical analysis of formality in online communication
E Pavlick, J Tetreault
Transactions of the Association for Computational Linguistics 4, 61-74, 2016
Collecting diverse natural language inference problems for sentence representation evaluation
A Poliak, A Haldar, R Rudinger, JE Hu, E Pavlick, AS White, B Van Durme
arXiv preprint arXiv:1804.08207, 2018
The language demographics of amazon mechanical turk
E Pavlick, M Post, A Irvine, D Kachaev, C Callison-Burch
Transactions of the Association for Computational Linguistics 2, 79-92, 2014
Simple PPDB: A Paraphrase Database for Simplification
E Pavlick, C Callison-Burch
Inherent disagreements in human textual inferences
E Pavlick, T Kwiatkowski
Transactions of the Association for Computational Linguistics 7, 677-694, 2019
Adding Semantics to Data-Driven Paraphrasing
E Pavlick, J Bos, M Nissim, C Beller, B Van Durme, C Callison-Burch
Proc. of ACL-IJCNLP. Beijing, China, 2015
Can you tell me how to get past sesame street? sentence-level pretraining beyond language modeling
A Wang, J Hula, P Xia, R Pappagari, RT McCoy, R Patel, N Kim, I Tenney, ...
arXiv preprint arXiv:1812.10860, 2018
Probing what different NLP tasks teach machines about function word comprehension
N Kim, R Patel, A Poliak, A Wang, P Xia, RT McCoy, I Tenney, A Ross, ...
arXiv preprint arXiv:1904.11544, 2019
Framenet+: Fast paraphrastic tripling of framenet
E Pavlick, T Wolfe, P Rastogi, C Callison-Burch, M Dredze, B Van Durme
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015
Inducing Lexical Style Properties for Paraphrase and Genre Differentiation
E Pavlick, A Nenkova
What Happens To BERT Embeddings During Fine-tuning?
A Merchant, E Rahimtoroghi, E Pavlick, I Tenney
arXiv preprint arXiv:2004.14448, 2020
Most babies are little and most problems are huge: Compositional Entailment in Adjective-Nouns
E Pavlick, C Callison-Burch
jiant 1.2: A software toolkit for research on general-purpose text understanding models
A Wang, IF Tenney, Y Pruksachatkun, K Yu, J Hula, P Xia, R Pappagari, ...
Note: http://jiant. info/Cited by: footnote 4, 2019
Are two heads better than one? crowdsourced translation via a two-step collaboration of non-professional translators and editors
R Yan, M Gao, E Pavlick, C Callison-Burch
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
The Gun Violence Database: A new task and data set for NLP
E Pavlick, H Ji, X Pan, C Callison-Burch
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