activity
20152021
most citedCodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

416 citations · 958 across the 23 of their papers we have counts for

collaborators
Showing 2020Show all

10 papers · 1 filter

cs.SE20208 cited

Multi-task Learning based Pre-trained Language Model for Code Completion

Fang Liu, Ge Li, Yunfei Zhao +1

Code completion is one of the most useful features in the Integrated Development Environments (IDEs), which can accelerate software development by suggesting the next probable toke…

cs.CV202013 cited

SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains

Yuanqi Chen, Ge Li, Cece Jin +2

This paper observes that there is an issue of high frequencies missing in the discriminator of standard GAN, and we reveal it stems from downsampling layers employed in the network…

cs.CV2020

Point Cloud Attribute Compression via Successive Subspace Graph Transform

Yueru Chen, Yiting Shao, Jing Wang +2

Inspired by the recently proposed successive subspace learning (SSL) principles, we develop a successive subspace graph transform (SSGT) to address point cloud attribute compressio…

cs.SE2020

Retrieve and Refine: Exemplar-based Neural Comment Generation

Bolin Wei, Yongmin Li, Ge Li +2

Code comment generation which aims to automatically generate natural language descriptions for source code, is a crucial task in the field of automatic software development. Tradit…

cs.SE20208 cited

Towards Full-line Code Completion with Neural Language Models

Wenhan Wang, Sijie Shen, Ge Li +1

A code completion system suggests future code elements to developers given a partially-complete code snippet. Code completion is one of the most useful features in Integrated Devel…

cs.CV2020

Toward Zero-Shot Unsupervised Image-to-Image Translation

Yuanqi Chen, Xiaoming Yu, Shan Liu +1

Recent studies have shown remarkable success in unsupervised image-to-image translation. However, if there has no access to enough images in target classes, learning a mapping from…