Reasoning about Entailment with Neural Attention
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Summary
This paper proposes a neural model that reads two sentences to determine entailment using long short-term memory units and extends this model with a word-by-word neural attention mechanism that encourages reasoning over entailments of pairs of words and phrases, and presents a qualitative analysis of attention weights produced by this model.
- Type
- preprint
- Published
- 2015-09-22
- Cited by
- 779
- References
- 34
- Access
- Open access
- OpenAlex
- https://openalex.org/W2118463056
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2135897
Keywords
Textual entailment, Logical consequence, Artificial intelligence, Computer science, Classifier (UML)
References
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- Long Short-Term Memory
- 2005 Special Issue: Framewise phoneme classification with bidirectional LSTM and other neural network architectures
- Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
- Representing Meaning with a Combination of Logical Form and Vectors
- ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment
- NaturalLI: Natural Logic Inference for Common Sense Reasoning
- Distributed Representations of Words and Phrases and their Compositionality
- Convolutional Neural Network Architectures for Matching Natural Language Sentences
- UNAL-NLP: Combining Soft Cardinality Features for Semantic Textual Similarity, Relatedness and Entailment
- SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment
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- Learning Word Meta-Embeddings by Using Ensembles of Embedding Sets
- ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
- From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
- Attentive Pooling Networks
- Long Short-Term Memory-Networks for Machine Reading
- Representation of Linguistic Form and Function in Recurrent Neural Networks
- Recurrent Neural Network Encoder with Attention for Community Question Answering
- Sentence Pair Scoring: Towards Unified Framework for Text Comprehension
- A Fast Unified Model for Parsing and Sentence Understanding
- Learning to Respond with Deep Neural Networks for Retrieval-Based Human-Computer Conversation System
- A Deep Neural Network for Chinese Zero Pronoun Resolution
- Semi-supervised Question Retrieval with Gated Convolutions
- Why and How to Pay Different Attention to Phrase Alignments of Different Intensities
- Modelling Interaction of Sentence Pair with Coupled-LSTMs
- Joint Learning of Sentence Embeddings for Relevance and Entailment
- Generating Natural Language Inference Chains
- Multimodal Residual Learning for Visual QA
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