A Systematic Assessment of Syntactic Generalization in Neural Language Models
While state-of-the-art neural network models continue to achieve lower perplexity scores on language modeling benchmarks, it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge. Furthermore, existing work has not provided a clear pictu...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for Computational Linguistics (ACL)
2021
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| Online Access: | https://hdl.handle.net/1721.1/130402 |