The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Does String-Based Neural MT Learn Source Syntax?
Open accessAbstract
We investigate whether a neural, encoderdecoder translation system learns syntactic information on the source side as a by-product of training.We propose two methods to detect whether the encoder has learned local and global source syntax.A fine-grained analysis of the syntactic structure learned by the encoder reveals which kinds of syntax are learned and which are missing.
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Sequence to Sequence Learning with Neural Networks
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Convolutional Neural Networks for Sentence Classification
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Building a Large Annotated Corpus of English: The Penn Treebank
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Cited by
What Does BERT Look at? An Analysis of BERT’s Attention
Clark, K., Khandelwal, U., Levy, O., & Manning, C. D. (2019) · Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP · doi:10.18653/v1/w19-4828 · Cited by 1,373
BERT Rediscovers the Classical NLP Pipeline
Tenney, I., Das, D., & Pavlick, E. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1452 · Cited by 1,307
Neural Network Acceptability Judgments
Warstadt, A., Singh, A., & Bowman, S. R. (2019) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00290 · Cited by 1,215
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Voita, E., Talbot, D., Moiseev, F., Sennrich, R., & Titov, I. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1580 · Cited by 1,146
How Can We Know What Language Models Know?
Jiang, Z., Xu, F. F., Araki, J., & Neubig, G. (2020) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00324 · Cited by 1,002
Metadata
- Authors
- Shi, X., Padhi, I., & Knight, K.
- Venue
- Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
- Published
- 2016
- Pages
- 1526-1534
- OpenAlex
- W2563574619
- Cited by
- 300
- References
- 23
- FWCI
- 23.96
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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