activity
20222026
most citedAn Empirical Study of AI Techniques in Mobile Applications

8 citations · 8 across the 11 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.CL2022

Moto: Enhancing Embedding with Multiple Joint Factors for Chinese Text Classification

Xunzhu Tang, Rujie Zhu, Tiezhu Sun +1

Recently, language representation techniques have achieved great performances in text classification. However, most existing representation models are specifically designed for Eng…

cs.CL2022

CKG: Dynamic Representation Based on Context and Knowledge Graph

Xunzhu Tang, Tiezhu Sun, Rujie Zhu +1

Recently, neural language representation models pre-trained on large corpus can capture rich co-occurrence information and be fine-tuned in downstream tasks to improve the performa…

cs.SE2022

DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android Bytecode

Tiezhu Sun, Kevin Allix, Kisub Kim +5

The automation of a large number of software engineering tasks is becoming possible thanks to Machine Learning (ML). Central to applying ML to software artifacts (like source or ex…

cs.SE2022★ 8 cited

An Empirical Study of AI Techniques in Mobile Applications

Yinghua Li, Xueqi Dang, Haoye Tian +5

The integration of artificial intelligence (AI) into mobile applications has significantly transformed various domains, enhancing user experiences and providing personalized servic…

cs.SE2022

MetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning

Weiguo Pian, Hanyu Peng, Xunzhu Tang +5

Representation learning of source code is essential for applying machine learning to software engineering tasks. Learning code representation from a multilingual source code datase…