Naomi Saphra
Naomi Saphra
Kempner Institute at Harvard University
Verified email at - Homepage
Cited by
Cited by
Dynet: The dynamic neural network toolkit
G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ...
arXiv preprint arXiv:1701.03980, 2017
Understanding objects in detail with fine-grained attributes
A Vedaldi, S Mahendran, S Tsogkas, S Maji, R Girshick, J Kannala, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2014
Understanding learning dynamics of language models with SVCCA
N Saphra, A Lopez
arXiv preprint arXiv:1811.00225, 2018
Understanding privacy-related questions on stack overflow
M Tahaei, K Vaniea, N Saphra
Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020
The multiberts: Bert reproductions for robustness analysis
T Sellam, S Yadlowsky, J Wei, N Saphra, A D'Amour, T Linzen, J Bastings, ...
arXiv preprint arXiv:2106.16163, 2021
A taxonomy and review of generalization research in NLP
D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ...
Nature Machine Intelligence 5 (10), 1161-1174, 2023
An algerian arabic-french code-switched corpus
R Cotterell, A Renduchintala, N Saphra, C Callison-Burch
Workshop on free/open-source arabic corpora and corpora processing tools …, 2014
Pareto probing: Trading off accuracy for complexity
T Pimentel, N Saphra, A Williams, R Cotterell
arXiv preprint arXiv:2010.02180, 2020
Linear connectivity reveals generalization strategies
J Juneja, R Bansal, K Cho, J Sedoc, N Saphra
arXiv preprint arXiv:2205.12411, 2022
A framework for (under) specifying dependency syntax without overloading annotators
N Schneider, B O'Connor, N Saphra, D Bamman, M Faruqui, NA Smith, ...
arXiv preprint arXiv:1306.2091, 2013
A non-linear structural probe
JC White, T Pimentel, N Saphra, R Cotterell
arXiv preprint arXiv:2105.10185, 2021
LSTMs compose (and learn) bottom-up
N Saphra, A Lopez
arXiv preprint arXiv:2010.04650, 2020
Benchmarking compositionality with formal languages
J Valvoda, N Saphra, J Rawski, A Williams, R Cotterell
arXiv preprint arXiv:2208.08195, 2022
Sudden drops in the loss: Syntax acquisition, phase transitions, and simplicity bias in mlms
A Chen, R Schwartz-Ziv, K Cho, ML Leavitt, N Saphra
arXiv preprint arXiv:2309.07311, 2023
Language models learn pos first
N Saphra, A Lopez
Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and …, 2018
Amrica: an amr inspector for cross-language alignments
N Saphra, A Lopez
Proceedings of the 2015 conference of the north american chapter of the …, 2015
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models
N Saphra, E Fleisig, K Cho, A Lopez
arXiv preprint arXiv:2311.05020, 2023
Training dynamics of neural language models
N Saphra
The University of Edinburgh, 2021
Evaluating Informal-Domain Word Representations With UrbanDictionary
N Saphra, A Lopez
The First Workshop on Evaluating Vector Space Representations for NLP, 2016
Dynamic masking rate schedules for mlm pretraining
Z Ankner, N Saphra, D Blalock, J Frankle, ML Leavitt
arXiv preprint arXiv:2305.15096, 2023
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