Improved code summarization via a graph neural network
Automatic source code summarization is the task of generating natural language
descriptions for source code. Automatic code summarization is a rapidly expanding research …
descriptions for source code. Automatic code summarization is a rapidly expanding research …
Universal dependency parsing from scratch
This paper describes Stanford's system at the CoNLL 2018 UD Shared Task. We introduce a
complete neural pipeline system that takes raw text as input, and performs all tasks required …
complete neural pipeline system that takes raw text as input, and performs all tasks required …
Glyce: Glyph-vectors for chinese character representations
It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the
use of the glyph information in those languages. However, due to the lack of rich …
use of the glyph information in those languages. However, due to the lack of rich …
Semantic neural machine translation using AMR
It is intuitive that semantic representations can be useful for machine translation, mainly
because they can help in enforcing meaning preservation and handling data sparsity (many …
because they can help in enforcing meaning preservation and handling data sparsity (many …
Transforming question answering datasets into natural language inference datasets
Existing datasets for natural language inference (NLI) have propelled research on language
understanding. We propose a new method for automatically deriving NLI datasets from the …
understanding. We propose a new method for automatically deriving NLI datasets from the …
Is word segmentation necessary for deep learning of Chinese representations?
Segmenting a chunk of text into words is usually the first step of processing Chinese text, but
its necessity has rarely been explored. In this paper, we ask the fundamental question of …
its necessity has rarely been explored. In this paper, we ask the fundamental question of …
Generating sentences from disentangled syntactic and semantic spaces
Variational auto-encoders (VAEs) are widely used in natural language generation due to the
regularization of the latent space. However, generating sentences from the continuous latent …
regularization of the latent space. However, generating sentences from the continuous latent …
Does syntax need to grow on trees? sources of hierarchical inductive bias in sequence-to-sequence networks
Learners that are exposed to the same training data might generalize differently due to
differing inductive biases. In neural network models, inductive biases could in theory arise …
differing inductive biases. In neural network models, inductive biases could in theory arise …
Hierarchy-aware global model for hierarchical text classification
Hierarchical text classification is an essential yet challenging subtask of multi-label text
classification with a taxonomic hierarchy. Existing methods have difficulties in modeling the …
classification with a taxonomic hierarchy. Existing methods have difficulties in modeling the …