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[PDF] Top 20 Sentence Modeling with Gated Recursive Neural Network

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Sentence Modeling with Gated Recursive Neural Network

Sentence Modeling with Gated Recursive Neural Network

... Inspired by grConv, we propose a gated recur- sive neural network (GRNN) for sentence model- ing. Different with grConv, we use the full binary tree (FBT) as the topological structure to ... See full document

6

Multi Perspective Sentence Similarity Modeling with Convolutional Neural Networks

Multi Perspective Sentence Similarity Modeling with Convolutional Neural Networks

... towards modeling with dis- tributed representations and neural network archi- ...volutional neural networks in a multitask setting, where their model is trained jointly for multiple NLP tasks ... See full document

11

A Recursive Recurrent Neural Network for Statistical Machine Translation

A Recursive Recurrent Neural Network for Statistical Machine Translation

... additive neural network for SMT decod- ...distortion modeling, Li et al. (2013) use recursive auto encoders to make full use of the entire merging phrase pairs, going beyond the boundary words ... See full document

10

A Sentence Interaction Network for Modeling Dependence between Sentences

A Sentence Interaction Network for Modeling Dependence between Sentences

... For sentence pair modeling, a simple idea is to first project the sentences to two sentence vectors separately with sentence modeling methods, and then feed these two vectors into other ... See full document

10

On Tree Based Neural Sentence Modeling

On Tree Based Neural Sentence Modeling

... tree-based sentence en- coders have shown better results on many downstream ...tree-based neural sentence ...tree modeling gives better results when crucial words are closer to the final ... See full document

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ABCNN: Attention Based Convolutional Neural Network for Modeling Sentence Pairs

ABCNN: Attention Based Convolutional Neural Network for Modeling Sentence Pairs

... on sentence repre- sentation learning while ARC-II focuses on match- ing features on phrase ...PI, sentence completion (SC) and tweet- response ...eral sentence matching based on phrase matching on ... See full document

14

Inter Weighted Alignment Network for Sentence Pair Modeling

Inter Weighted Alignment Network for Sentence Pair Modeling

... For sentence modeling, RNN (Elman, 1990; Mikolov et ...a sentence sequentially by updating the hidden state which represents context ...As sentence length grows, RNN will suffer from gradient ... See full document

11

Convolution Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling

Convolution Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling

... feedforward neural network to model phrase embeddings and try to maximize their semantic similarity, while Zhang et ...recently, neural machine translation trains a unified encoder-decoder (Sutskever ... See full document

11

Character Based Neural Networks for Sentence Pair Modeling

Character Based Neural Networks for Sentence Pair Modeling

... the effective design of the BiLSTM and word in- teraction layers, as well as the unique character of sentence pair modeling, where n-gram over- lapping positively signifies the extent of seman- tic ... See full document

7

Unsupervised Latent Tree Induction with Deep Inside Outside Recursive Auto Encoders

Unsupervised Latent Tree Induction with Deep Inside Outside Recursive Auto Encoders

... To test the impact of our modeling choices, we compared the performance of two different losses and four different composition functions on the full WSJ validation set. The losses were covered in Equations 1 ... See full document

13

Cluster Gated Convolutional Neural Network for Short Text Classification

Cluster Gated Convolutional Neural Network for Short Text Classification

... convolutional neural network (CNN) architecture that utilized multiple parallel convolutional layers with varying filter window sizes and concatenated the selected important features into a dense softmax ... See full document

10

A Dependency Based Neural Network for Relation Classification

A Dependency Based Neural Network for Relation Classification

... a neural network ...two neural networks are used to model shortest dependency paths and dependency subtrees ...convolutional neural network (CNN) is applied over the shortest dependency ... See full document

6

Discourse Relation Recognition by Comparing Various Units of Sentence Expression with Recursive Neural Network

Discourse Relation Recognition by Comparing Various Units of Sentence Expression with Recursive Neural Network

... In the example in Table 3, the inputs classified correctly by all methods were identified by extract- ing the characteristic content words from each ut- terance. For example, in the first example, the re- lation is ... See full document

10

Discriminative Neural Sentence Modeling by Tree Based Convolution

Discriminative Neural Sentence Modeling by Tree Based Convolution

... used neural sentence models are convolutional neural networks (CNNs) and recur- sive neural networks ...ent sentence structures ...by recursive semantic composition along a parse ... See full document

11

Attentive Gated Lexicon Reader with Contrastive Contextual Co Attention for Sentiment Classification

Attentive Gated Lexicon Reader with Contrastive Contextual Co Attention for Sentiment Classification

... into neural network for the task of sentiment anal- ...supporting network aims to learn a ‘lexicon-based’ view of the sentence and can be interpreted as ‘learning to compose’ by ex- ploiting ... See full document

11

Dependency based Gated Recursive Neural Network for Chinese Word Segmentation

Dependency based Gated Recursive Neural Network for Chinese Word Segmentation

... models. Neural network models have the advantage of minimiz- ing the effort in feature ...general neural network ar- chitecture for sequence labeling ...work, neural network ... See full document

6

Segment Level Sequence Modeling using Gated Recursive Semi Markov Conditional Random Fields

Segment Level Sequence Modeling using Gated Recursive Semi Markov Conditional Random Fields

... For non-neural models, JESS-CM (Suzuki and Isozaki, 2008) is a semi-supervised model which combines Hidden Markov Models (HMMs) with CRFs and uses 1 billion unlabelled words in train- ing. Lin and Wu (2009) ... See full document

11

Gated Recursive Neural Network for Chinese Word Segmentation

Gated Recursive Neural Network for Chinese Word Segmentation

... a sentence “ 雨 (Rainy) 天 (Day) 地面 (Ground) 积水 (Accumu- lated water)”, the target character is ...This sentence is very complicated because each consec- utive two characters can be combined as a ... See full document

10

Document Modeling with Gated Recurrent Neural Network for Sentiment Classification

Document Modeling with Gated Recurrent Neural Network for Sentiment Classification

... Recently, neural network e- merges as an effective way to learn continuous text representation for sentiment ...sive neural networks for sentence-level semantic composition. Recursive ... See full document

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Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks

Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks

... However, most of the existing neural network based methods still need some efforts in feature engineering. For example, most methods often se- lect the first and second leftmost/rightmost chil- dren of the ... See full document

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