The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Subword units are an effective way to alleviate the open vocabulary problems in neural
machine translation (NMT). While sentences are usually converted into unique subword …

We investigate a lattice-structured LSTM model for Chinese NER, which encodes a
sequence of input characters as well as all potential words that match a lexicon. Compared …

The automatic detection of software vulnerabilities is an important research problem.
However, existing solutions to this problem rely on human experts to define features and …

摘要机器翻译研究将源语言所表达的语义自动转换为目标语言的相同语义,
是人工智能和自然语言处理的重要研究内容. 近年来, 基于序列到序列模型(Sequence-to …

Chinese relation extraction is conducted using neural networks with either character-based
or word-based inputs, and most existing methods typically suffer from segmentation errors …

Vulnerability detection using machine learning is a hot topic in improving software security.
However, existing works formulate detection as a classification problem, which requires a …

Security patches, embedding both vulnerable code and the corresponding fixes, are of great
significance to vulnerability detection and software maintenance. However, the existing …

Incorporating lexicons into character-level Chinese NER by lattices is proven effective to
exploitrich word boundary information. Previous work has extended RNNs to consume …

Current spoken language understanding systems heavily rely on the best hypothesis (ASR 1-
best) generated by automatic speech recognition, which is used as the input for downstream …