[PDF] Top 20 Summarizing Source Code using a Neural Attention Model
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Summarizing Source Code using a Neural Attention Model
... end-to-end neural network called CODE-NN that jointly performs content selection using an attention mechanism, and surface realization using Long Short Term Memory (LSTM) ...the ... See full document
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A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes
... a model to automatically de- scribe changes introduced in the source code of a program using natural ...of code commits, which contains both the modifi- cations and message introduced ... See full document
6
A Nested Attention Neural Hybrid Model for Grammatical Error Correction
... (S2S) model which encodes a sequence of source words into a vector and then generates a sequence of target words from the vec- ...S2S model can capture long-distance, or even global, word ... See full document
10
Look Harder: A Neural Machine Translation Model with Hard Attention
... NMT model (Vaswani et al., 2017). The proposed model solely selects a few relevant to- kens across the entire source sequence for each target token to effectively handle long sequence ...NMT ... See full document
7
Target Foresight Based Attention for Neural Machine Translation
... in neural machine translation, an attention model is used to identify the aligned source words for a target word target foresight word in order to select translation con- text, but it does not ... See full document
11
An Unsupervised Neural Attention Model for Aspect Extraction
... in using such automated ...en- code word co-occurrence statistics which are the primary source of information to preserve topic coherence (Mimno et ... See full document
10
A Syntactic Neural Model for General Purpose Code Generation
... with neural network-based approaches re- cently explored (Liu et ...general-purpose code generation, besides the general framework of Ling et ...for code re- trieval (Wei et ...from source ... See full document
11
A Visual Attention Grounding Neural Model for Multimodal Machine Translation
... translation model, and (2) constructing a vision-language joint semantic ...this model, we develop a visual attention mechanism to learn an attention vector that values the words that have ... See full document
11
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings
... seq2seq model incorrectly aligns the target side end of sentence mark eos to 下旬 /late with a high attention weight ...the source word 下旬 /late and the target ...to source side ... See full document
10
Source Code Summarization of Context for Java Source Code
... Automatic source code summarization has begun to emerge as a means of helping authors expedite the documentation process [7], [8], [9], [10], [11], [12], ...acquired using a vectorspace model ... See full document
6
Deep Learning Approach for Text Generation Using RNN Encoder-Decoder for Q&A
... of neural network based on encoder and decoder for machine translation and new type of cell called Gated Recurrent Unit ...The neural network proposed in article encodes source language sentence in ... See full document
6
DCU UvA Multimodal MT System Report
... a model which incorporates multi- ple multimodal attention mechanisms into a neu- ral machine translation ...decoder. Source language and visual attention mechanisms have been well- studied in ... See full document
5
Co-Attention Based Neural Network for Source-Dependent Essay Scoring
... based neural network model that outperforms a state of the art attention based neural network model for essay scoring, not only for RTA Evidence assess- ment but also for holistic ... See full document
11
Hindi-English Neural Machine Translation Using Attention Model
... both source and target languages) when machine translation is Less Expensive as compared to Humans and can be found at a click of a button by every device like laptop, mobile, ...our Neural Machine ... See full document
5
Detecting Adverse Drug Reactions from Biomedical Texts with Neural Networks
... analysis, neural networks are popularly utilized (Zhang et ...Interactive Attention Network which interactively learns attentions in the contexts and targets, and generates the representations for tar- gets ... See full document
7
A Neural Attention Model for Disfluency Detection
... detection using the encoder-decoder ...a neural attention- based model which can efficiently model the long-range dependencies between words and make the resulting sentence more likely ... See full document
10
A Neural Model for Language Identification in Code Switched Tweets
... There are three differences between our version of the model and the one described by Kim et al. (2016). First, we use two layers of convolution in- stead of just one, inspired by Ling et al. (2015a) which uses a ... See full document
5
Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach
... The EOF analysis (Fig. 11) extracts the spatiotemporal similarities and dissimilarities between the two different DK- model configurations. The analysis is based on monthly mean maps generated using the ... See full document
19
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
... Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, ukasz Kaiser, Stephan ... See full document
12
A Hybrid Weighted Probabilistic Based Source Code Graph Clustering Algorithm For Class Diagram And Sequence Diagram Visualization
... (the source lines can be ...low-level source code layout ...of model regeneration is to remove module-level dependence from the source code and store the results in a ... See full document
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