Yonatan Belinkov
Synthetic and natural noise both break neural machine translation
Y Belinkov, Y Bisk
arXiv preprint arXiv:1711.02173, 2017
Linguistic knowledge and transferability of contextual representations
NF Liu, M Gardner, Y Belinkov, ME Peters, NA Smith
arXiv preprint arXiv:1903.08855, 2019
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Y Adi, E Kermany, Y Belinkov, O Lavi, Y Goldberg
arXiv preprint arXiv:1608.04207, 2016
Analysis methods in neural language processing: A survey
Y Belinkov, J Glass
Transactions of the Association for Computational Linguistics 7, 49-72, 2019
What do neural machine translation models learn about morphology?
Y Belinkov, N Durrani, F Dalvi, H Sajjad, J Glass
arXiv preprint arXiv:1704.03471, 2017
Analyzing the structure of attention in a transformer language model
J Vig, Y Belinkov
arXiv preprint arXiv:1906.04284, 2019
Bloom: A 176b-parameter open-access multilingual language model
TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
arXiv preprint arXiv:2211.05100, 2022
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Evaluating layers of representation in neural machine translation on part-of-speech and semantic tagging tasks
Y Belinkov, L Màrquez, H Sajjad, N Durrani, F Dalvi, J Glass
arXiv preprint arXiv:1801.07772, 2018
Investigating gender bias in language models using causal mediation analysis
J Vig, S Gehrmann, Y Belinkov, S Qian, D Nevo, Y Singer, S Shieber
Advances in neural information processing systems 33, 12388-12401, 2020
Identifying and Controlling Important Neurons in Neural Machine Translation
A Bau, Y Belinkov, H Sajjad, N Durrani, F Dalvi, J Glass
International Conference on Learning Representations, 2019
What is one grain of sand in the desert? analyzing individual neurons in deep nlp models
F Dalvi, N Durrani, H Sajjad, Y Belinkov, A Bau, J Glass
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6309-6317, 2019
End-to-end bias mitigation by modelling biases in corpora
RK Mahabadi, Y Belinkov, J Henderson
arXiv preprint arXiv:1909.06321, 2019
Probing classifiers: Promises, shortcomings, and advances
Y Belinkov
Computational Linguistics 48 (1), 207-219, 2022
A constructive prediction of the generalization error across scales
JS Rosenfeld, A Rosenfeld, Y Belinkov, N Shavit
arXiv preprint arXiv:1909.12673, 2019
Don't take the premise for granted: Mitigating artifacts in natural language inference
Y Belinkov, A Poliak, SM Shieber, B Van Durme, AM Rush
arXiv preprint arXiv:1907.04380, 2019
Locating and editing factual associations in GPT
K Meng, D Bau, A Andonian, Y Belinkov
Advances in Neural Information Processing Systems 35, 17359-17372, 2022
Analyzing hidden representations in end-to-end automatic speech recognition systems
Y Belinkov, J Glass
Advances in Neural Information Processing Systems 30, 2017
Arabic diacritization with recurrent neural networks
Y Belinkov, J Glass
Proceedings of the 2015 Conference on Empirical Methods in Natural Language …, 2015
Understanding and improving morphological learning in the neural machine translation decoder
F Dalvi, N Durrani, H Sajjad, Y Belinkov, S Vogel
Proceedings of the Eighth International Joint Conference on Natural Language …, 2017
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