Textual entailment with structured attentions and composition

COLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers

Volumn , Issue , 2016, Pages 2248-2258

  Zhao, Kai ^a   Huang, Liang ^a   Ma, Mingbo ^a  

^a 1148 Kelley Engineering Center Corvallis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; TEXT PROCESSING;

ATTENTION MODEL; COMPOSITION MODEL; DISCRETE MODELS; LEARNING TECHNIQUES; NATURAL LOGIC; STATE OF THE ART; TEXTUAL ENTAILMENT; WORD ALIGNMENT;

DEEP LEARNING;

EID: 85050983881     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Jimmy Ba, Ruslan R Salakhutdinov, Roger B Grosse, and Brendan J Frey. 2015. Learning wake-sleep recurrent attention models. In Advances in Neural Information Processing Systems, pages 2575-2583.
2. Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv: 1409.0473.
3. Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 632-642, Lisbon, Portugal, September. Association for Computational Linguistics.
4. Jianpeng Cheng, Li Dong, and Mirella Lapata. 2016. Long short-term memory-networks for machine reading. arXiv preprint arXiv: 1601.06733.
5. Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, Kaisheng Yao, Chris Dyer, and Gholamreza Haffari. 2016. Incorporating structural alignment biases into an attentional neural translation model. arXiv preprint arXiv: 1601.01085.
6. Robin Cooper, Dick Crouch, Jan Van Eijck, Chris Fox, Johan Van Genabith, Jan Jaspars, Hans Kamp, David Milward, Manfred Pinkal, Massimo Poesio, et al. 1996. Using the framework. Technical report, Technical Report LRE 62-051 D-16, The FraCaS Consortium.
7. Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006. The pascal recognising textual entailment challenge. In Machine learning challenges, evaluating predictive uncertainty, visual object classification, and recognising tectual entailment, pages 177-190. Springer.
8. Simone Filice, Giovanni Da San Martino, and Alessandro Moschitti. 2015. Structural representations for learning relations between pairs of texts. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics, Beijing, China, July. Association for Computational Linguistics.
9. Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short-term memory. Neural computation, 9(8): 1735-1780.
10. Diederik Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv: 1412.6980.
11. Bill MacCartney and Christopher D Manning. 2009. An extended model of natural logic. In Proceedings of the eighth international conference on computational semantics, pages 140-156. Association for Computational Linguistics.
12. Volodymyr Mnih, Nicolas Heess, Alex Graves, et al. 2014. Recurrent models of visual attention. In Advances in Neural Information Processing Systems, pages 2204-2212.
13. Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. Glove: Global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), pages 1532-1543.
14. Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomas Kocisky, and Phil Blunsom. 2015. Reasoning about entailment with neural attention. arXiv preprint arXiv: 1509.06664.
15. Richard Socher, Alex Perelygin, Jean Y Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of the conference on empirical methods in natural language processing (EMNLP), Volume 1631, page 1642. Citeseer.
16. Kai Sheng Tai, Richard Socher, and Christopher D. Manning. 2015. Improved semantic representations from tree-structured long short-term memory networks. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1556-1566, Beijing, China, July. Association for Computational Linguistics.
17. Ran Tian, Yusuke Miyao, and Takuya Matsuzaki. 2014. Logical inference on dependency-based compositional semantics. In Proceedings of ACL, pages 79-89.
18. Shuohang Wang and Jing Jiang. 2015. Learning natural language inference with 1stm. arXiv preprint arXiv: 1512.08849.
19. Mengqiu Wang and Christopher D Manning. 2010. Probabilistic tree-edit models with structured latent variables for textual entailment and question answering. In Proceedings of the 23rd International Conference on Computational Linguistics, pages 1164-1172. Association for Computational Linguistics.
20. Yotaro Watanabe, Junta Mizuno, Eric Nichols, Naoaki Okazaki, and Kentaro Inui. 2012. A latent discriminative model for compositional entailment relation recognition using natural logic. In COLING, pages 2805-2820.
21. Kelvin Xu, Jimmy Ba, Ryan Kiros, Aaron Courville, Ruslan Salakhutdinov, Richard Zemel, and Yoshua Bengio. 2015. Show, attend and tell: Neural image caption generation with visual attention. arXiv preprint arXiv: 1502.03044.
22. Fabio Massimo Zanzotto, Marco Pennacchiotti, and Alessandro Moschitti. 2009. A machine learning approach to textual entailment recognition. Natural Language Engineering, 15(04): 551-582.
23. Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals. 2014. Recurrent neural network regularization. arXiv preprint arXiv: 1409.2329.