978 citations · 2.5k across the 33 of their papers we have counts for
5 papers · 1 filter
Soft-Labeled Contrastive Pre-training for Function-level Code Representation
Xiaonan Li, Daya Guo, Yeyun Gong +6
Code contrastive pre-training has recently achieved significant progress on code-related tasks. In this paper, we present \textbf{SCodeR}, a \textbf{S}oft-labeled contrastive pre-t…
LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval
Canwen Xu, Daya Guo, Nan Duan +1
In this paper, we propose LaPraDoR, a pretrained dual-tower dense retriever that does not require any supervised data for training. Specifically, we first present Iterative Contras…
ReACC: A Retrieval-Augmented Code Completion Framework
Shuai Lu, Nan Duan, Hojae Han +3
Code completion, which aims to predict the following code token(s) according to the code context, can improve the productivity of software development. Recent work has proved that…
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
Daya Guo, Shuai Lu, Nan Duan +3
Pre-trained models for programming languages have recently demonstrated great success on code intelligence. To support both code-related understanding and generation tasks, recent…
Automating Code Review Activities by Large-Scale Pre-training
Zhiyu Li, Shuai Lu, Daya Guo +8
Code review is an essential part to software development lifecycle since it aims at guaranteeing the quality of codes. Modern code review activities necessitate developers viewing,…