most citedNatural Attack for Pre-trained Models of Code

163 citations · 218 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DC202211 cited

FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server

Hong Zhang, Ji Liu, Juncheng Jia +3

Despite achieving remarkable performance, Federated Learning (FL) suffers from two critical challenges, i.e., limited computational resources and low training efficiency. In this p…

cs.SE202243 cited

PTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained Models

Junda He, Bowen Xu, Zhou Yang +3

Stack Overflow is often viewed as the most influential Software Question Answer (SQA) website with millions of programming-related questions and answers. Tags play a critical role…

cs.SE2022163 cited

Natural Attack for Pre-trained Models of Code

Zhou Yang, Jieke Shi, Junda He +1

Pre-trained models of code have achieved success in many important software engineering tasks. However, these powerful models are vulnerable to adversarial attacks that slightly pe…

cs.SE20221 cited

Aspect-Based API Review Classification: How Far Can Pre-Trained Transformer Model Go?

chengran Yang, Bowen Xu, Junaed younus Khan +4

APIs (Application Programming Interfaces) are reusable software libraries and are building blocks for modern rapid software development. Previous research shows that programmers fr…

cs.SE2022

Can Identifier Splitting Improve Open-Vocabulary Language Model of Code?

Jieke Shi, Zhou Yang, Junda He +2

Statistical language models on source code have successfully assisted software engineering tasks. However, developers can create or pick arbitrary identifiers when writing source c…

cs.DC2021

Efficient Device Scheduling with Multi-Job Federated Learning

Chendi Zhou, Ji Liu, Juncheng Jia +4

Recent years have witnessed a large amount of decentralized data in multiple (edge) devices of end-users, while the aggregation of the decentralized data remains difficult for mach…