Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
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Summary
The Tree-LSTM is introduced, a generalization of LSTMs to tree-structured network topologies that outperform all existing systems and strong LSTM baselines on two tasks: predicting the semantic relatedness of two sentences and sentiment classification.
- Type
- preprint
- Published
- 2015-02-27
- Cited by
- 3,273
- References
- 41
- Access
- Open access
- OpenAlex
- https://openalex.org/W2104246439
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3033526
Keywords
Computer science, Treebank, Artificial intelligence, Natural language processing, Recurrent neural network
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- Tree-Structured Composition in Neural Networks without Tree-Structured Architectures
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- Towards Universal Paraphrastic Sentence Embeddings
- A Generative Model of Words and Relationships from Multiple Sources
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