sequence model
Hidden Softmax Sequence Model for Dialogue Structure Analysis
... learning model, hidden softmax sequence model (HSSM), based on Boltzmann machine for dialogue structure ...The model employs three types of units in the hidden layer to discovery dialogue ...
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Generating Video Description using Sequence to sequence Model with Temporal Attention
... encoder-decoder sequence-to-sequence model with temporal attention ...encoder-decoder sequence-to-sequence model and are able to outperform the state-of-the-art system on ...
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A Graph to Sequence Model for AMR to Text Generation
... the sequence-to-sequence model (Sutskever et ...of sequence-to-sequence models, however, is that they require serialization of input AMR graphs, which adds to the challenge of ...
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A Sequence to Sequence Model for Semantic Role Labeling
... seq2seq model with attention in a monolingual SRL labeling setup, we need to restrict the decoder to reproduce the original input sentence, while in addition inserting PropBank la- bels into the target ...
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Implementation of Recurrent Neural Network with Sequence to Sequence Model to Translate Language Based on TensorFlow
... language model that deals with textual data regarding a multi-dimensional data with respect to the input of the ...this model was taken from the META data set database with low velocity than MNIST dataset ...
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A Sequence Model Approach to Relation Extraction in Portuguese
... In this paper, we use relation-specific features for Por- tuguese described in previous work (Collovini et al., 2014). The sets of features are: Part-Of-Speech (e. g. POS tag); lexical (e. g. canonic form), syntactic (e. ...
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An Operation Sequence Model for Explainable Neural Machine Translation
... slightly worse on es-en. We think that more engi- neering work such as optimizing the set of oper- ations or improving the training alignments could lead to more consistent gains from using OSNMT. However, we leave this ...
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Character Sequence to Sequence Model with Global Attention for Universal Morphological Reinflection
... Another difference from machine translation is that our input and output sequence characters may be very similar except the inflections. Take the words release, releasing, and released from En- glish as an ...
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GECOR: An End to End Generative Ellipsis and Co reference Resolution Model for Task Oriented Dialogue
... semantic sequence model to learn semantic patterns and a syntactic sequence model to learn linguistic patterns to tackle with the non-sentential (incomplete) questions in a question answering ...
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MT/IE: Cross lingual Open Information Extraction with Neural Sequence to Sequence Models
... a sequence-to-sequence model that enables end-to- end cross-lingual Open ...the model encodes natural-language sentences and decodes predicate-argument forms (Figure ...neural model is ...
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A Sequence Alignment Model Based on the Averaged Perceptron
... edit model on both data sets us- ing both the sampling procedure outlined above and the self-generation training regime, in each case for 20 epochs, producing models of orders from 1 to ...character ...
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A NEW TARGET FOR DIABETES: HOMOLOGY MODELING AND IDENTIFICATION OF POTENTIAL LEADS THROUGH VIRTUAL SCREENING
... of Sequence, Model Building, and Model Validation: MCT11 protein template sequence is searched against the known protein structures sequence and model building is performed using ...
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Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization
... the sequence-to-sequence model ...our model on a popular Chinese social media ...our model achieves the state-of-the-art performances on the benchmark ...
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DeepCopy: Grounded Response Generation with Hierarchical Pointer Networks
... attentional sequence-to-sequence model with a hierarchical pointer network that enables the decoder to jointly attend and copy tokens from any of the facts avail- able as external knowledge in ...
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Toward Data Driven Tutorial Question Answering with Deep Learning Conversational Models
... retrieval-based model of the dual encoder with the generative model of the se- quence-to-sequence ...this model was that a user typically asks questions with a length of fewer than 20 words ...
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Sequence to Sequence Mixture Model for Diverse Machine Translation
... recent attention (e.g., Vijayakumar et al. (2016); Li et al. (2016)). Given a source sentence, human translators are able to produce a set of diverse and reasonable translations. However, although beam search for S EQ 2S ...
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Iterative Recursive Attention Model for Interpretable Sequence Classification
... attention model (IRAM), where the result of an attentive query is nonlinearly transformed and then added to the set of vector representations of the in- put ...the model to construct a recursive ...
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A Hierarchical Word Sequence Language Model
... Most language models used for natural lan- guage processing are continuous. However, the assumption of such kind of models is too simple to cope with data sparsity problem. Al- though many useful smoothing techniques are ...
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Towards Generating Math Word Problems from Equations and Topics
... In this work, we present M A G N ET, a novel model for math word problem generation. It considers the input of both equations and topics using a fu- sion module. Additionally, an entity-enforced loss is introduced ...
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Hybrid Data Model Parallel Training for Sequence to Sequence Recurrent Neural Network Machine Translation
... with model parallelism became similar to those of our hybrid parallelism after long ...baseline model with model ...data- model parallel approach is faster than model par- allelism, and ...
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