9 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.SE2023★ 1 cited
Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases
Ze Tang, Jidong Ge, Shangqing Liu +4
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completi…
cs.SE2023★ 9 cited
Practical Program Repair via Preference-based Ensemble Strategy
Wenkang Zhong, Chuanyi Li, Kui Liu +5
To date, over 40 Automated Program Repair (APR) tools have been designed with varying bug-fixing strategies, which have been demonstrated to have complementary performance in terms…
cs.LG2023
Private Training Set Inspection in MLaaS
Mingxue Xu, Tongtong Xu, Po-Yu Chen
Machine Learning as a Service (MLaaS) is a popular cloud-based solution for customers who aim to use an ML model but lack training data, computation resources, or expertise in ML.…