A survey of automatic software vulnerability detection, program repair, and defect prediction techniques
Z Shen, S Chen - Security and Communication Networks, 2020 - Wiley Online Library
Open source software has been widely used in various industries due to its openness and
flexibility, but it also brings potential software security problems. Together with the large …
flexibility, but it also brings potential software security problems. Together with the large …
Named entity recognition with bidirectional LSTM-CNNs
JPC Chiu, E Nichols - … of the association for computational linguistics, 2016 - direct.mit.edu
Named entity recognition is a challenging task that has traditionally required large amounts
of knowledge in the form of feature engineering and lexicons to achieve high performance …
of knowledge in the form of feature engineering and lexicons to achieve high performance …
Deep learning code fragments for code clone detection
Code clone detection is an important problem for software maintenance and evolution. Many
approaches consider either structure or identifiers, but none of the existing detection …
approaches consider either structure or identifiers, but none of the existing detection …
Predicting the next location: A recurrent model with spatial and temporal contexts
Spatial and temporal contextual information plays a key role for analyzing user behaviors,
and is helpful for predicting where he or she will go next. With the growing ability of …
and is helpful for predicting where he or she will go next. With the growing ability of …
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
Natural language generation (NLG) is a critical component of spoken dialogue and it has a
significant impact both on usability and perceived quality. Most NLG systems in common use …
significant impact both on usability and perceived quality. Most NLG systems in common use …
Sequential short-text classification with recurrent and convolutional neural networks
JY Lee, F Dernoncourt - arXiv preprint arXiv:1603.03827, 2016 - arxiv.org
Recent approaches based on artificial neural networks (ANNs) have shown promising
results for short-text classification. However, many short texts occur in sequences (eg …
results for short-text classification. However, many short texts occur in sequences (eg …
A systematic literature review on the use of machine learning in code clone research
Context: Research related to code clones includes detection of clones in software systems,
analysis, visualization and management of clones. Detection of semantic clones and …
analysis, visualization and management of clones. Detection of semantic clones and …
On using monolingual corpora in neural machine translation
Recent work on end-to-end neural network-based architectures for machine translation has
shown promising results for En-Fr and En-De translation. Arguably, one of the major factors …
shown promising results for En-Fr and En-De translation. Arguably, one of the major factors …
[PDF][PDF] Lstm neural networks for language modeling.
Neural networks have become increasingly popular for the task of language modeling.
Whereas feed-forward networks only exploit a fixed context length to predict the next word of …
Whereas feed-forward networks only exploit a fixed context length to predict the next word of …
From feedforward to recurrent LSTM neural networks for language modeling
M Sundermeyer, H Ney… - IEEE/ACM Transactions on …, 2015 - ieeexplore.ieee.org
Language models have traditionally been estimated based on relative frequencies, using
count statistics that can be extracted from huge amounts of text data. More recently, it has …
count statistics that can be extracted from huge amounts of text data. More recently, it has …