On Decoding Strategies for Neural Text Generators
AbstractWhen generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text. Yet the properties elicited by various decoding strategies do not always transfer across natural language generation tasks. For example, while mode-seekin...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2022-01-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00502/113024/On-Decoding-Strategies-for-Neural-Text-Generators |