The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Bilateral Multi-Perspective Matching for Natural Language Sentences
Open accessAbstract
Natural language sentence matching is a fundamental technology for a variety of tasks. Previous approaches either match sentences from a single direction or only apply single granular (word-by-word or sentence-by-sentence) matching. In this work, we propose a bilateral multi-perspective matching (BiMPM) model. Given two sentences P and Q, our model first encodes them with a BiLSTM encoder. Next, we match the two encoded sentences in two directions P against Q and P against Q. In each matching direction, each time step of one sentence is matched against all time-steps of the other sentence from multiple perspectives. Then, another BiLSTM layer is utilized to aggregate the matching results into a fix-length matching vector. Finally, based on the matching vector, a decision is made through a fully connected layer. We evaluate our model on three tasks: paraphrase identification, natural language inference and answer sentence selection. Experimental results on standard benchmark datasets show that our model achieves the state-of-the-art performance on all tasks.
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SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK
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Order-Embeddings of Images and Language
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Minaee, S., Kalchbrenner, N., Cambria, E., Nikzad, N., Chenaghlu, M., & Gao, J. (2022) · ACM Computing Surveys · doi:10.1145/3439726 · Cited by 1,538
The Natural Language Decathlon: Multitask Learning as Question Answering
McCann, B., Keskar, N. S., Xiong, C., & Socher, R. (2018) · arXiv · doi:10.48550/arxiv.1806.08730 · Cited by 448
Challenges in building intelligent open-domain dialog systems
Huang, M., Zhu, X., & Gao, J. (2020) · ACM Transactions on Information Systems · doi:10.1145/3383123 · Cited by 288
Neural Natural Language Inference Models Enhanced with External Knowledge
Chen, Q., Zhu, X., Ling, Z.-H., Inkpen, D., & Wei, S. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p18-1224 · Cited by 253
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
Subramanian, S., Trischler, A., Bengio, Y., & Pal, C. J. (2018) · arXiv · doi:10.48550/arxiv.1804.00079 · Cited by 207
Metadata
- Authors
- Wang, Z., Hamza, W., & Florian, R.
- Venue
- Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
- Published
- 2017-08
- Pages
- 4144-4150
- OpenAlex
- W2593833795
- Cited by
- 739
- References
- 7
- FWCI
- 47.76
- Type
- conference paper
- Language
- en
- Open access
- bronze
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