Generating Sentences by Editing Prototypes

Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang


Abstract
We propose a new generative language model for sentences that first samples a prototype sentence from the training corpus and then edits it into a new sentence. Compared to traditional language models that generate from scratch either left-to-right or by first sampling a latent sentence vector, our prototype-then-edit model improves perplexity on language modeling and generates higher quality outputs according to human evaluation. Furthermore, the model gives rise to a latent edit vector that captures interpretable semantics such as sentence similarity and sentence-level analogies.
Anthology ID:
Q18-1031
Volume:
Transactions of the Association for Computational Linguistics, Volume 6
Month:
Year:
2018
Address:
Venue:
TACL
SIG:
Publisher:
Note:
Pages:
437–450
Language:
URL:
https://www.aclweb.org/anthology/Q18-1031
DOI:
10.1162/tacl_a_00030
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PDF:
http://aclanthology.lst.uni-saarland.de/Q18-1031.pdf
Video:
 https://vimeo.com/285801187