Recursive Neural Networks Can Learn Logical Semantics

Samuel R. Bowman, Christopher Potts, Christopher D. Manning


Anthology ID:
W15-4002
Volume:
Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality
Month:
July
Year:
2015
Address:
Beijing, China
Editors:
Alexandre Allauzen, Edward Grefenstette, Karl Moritz Hermann, Hugo Larochelle, Scott Wen-tau Yih
Venue:
CVSC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
12–21
Language:
URL:
https://aclanthology.org/W15-4002
DOI:
10.18653/v1/W15-4002
Bibkey:
Cite (ACL):
Samuel R. Bowman, Christopher Potts, and Christopher D. Manning. 2015. Recursive Neural Networks Can Learn Logical Semantics. In Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality, pages 12–21, Beijing, China. Association for Computational Linguistics.
Cite (Informal):
Recursive Neural Networks Can Learn Logical Semantics (Bowman et al., CVSC 2015)
Copy Citation:
PDF:
https://aclanthology.org/W15-4002.pdf
Poster:
 W15-4002.Poster.pdf
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