28 citations · 31 across the 5 of their papers we have counts for
5 papers
Envisioning the Next-Generation AI Coding Assistants: Insights & Proposals
Khanh Nghiem, Anh Minh Nguyen, Nghi D. Q. Bui
As a research-product hybrid group in AI for Software Engineering (AI4SE), we present four key takeaways from our experience developing in-IDE AI coding assistants. AI coding assis…
CodeT5+: Open Code Large Language Models for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Deepak Gotmare +3
Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations in terms of…
Better Language Models of Code through Self-Improvement
Hung Quoc To, Nghi D. Q. Bui, Jin Guo +1
Pre-trained language models for code (PLMCs) have gained attention in recent research. These models are pre-trained on large-scale datasets using multi-modal objectives. However, f…
Class based Influence Functions for Error Detection
Thang Nguyen-Duc, Hoang Thanh-Tung, Quan Hung Tran +4
Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we…
Energy-bounded Learning for Robust Models of Code
Nghi D. Q. Bui, Yijun Yu
In programming, learning code representations has a variety of applications, including code classification, code search, comment generation, bug prediction, and so on. Various repr…