4 citations · 11 across the 13 of their papers we have counts for
6 papers · 1 filter
Memory-Efficient Large Language Models for Program Repair with Semantic-Guided Patch Generation
Thanh Le-Cong, Bach Le, Toby Murray
In this paper, we first show that increases in beam size, even for small-sized LLMs (1B-7B params), require extensive GPU usage, leading to up to 80% of recurring crashes due to me…
Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection
Xin Zhou, Duc-Manh Tran, Thanh Le-Cong +5
Software vulnerabilities pose significant security challenges and potential risks to society, necessitating extensive efforts in automated vulnerability detection. There are two po…
VRDSynth: Synthesizing Programs for Multilingual Visually Rich Document Information Extraction
Thanh-Dat Nguyen, Tung Do-Viet, Hung Nguyen-Duy +5
Businesses need to query visually rich documents (VRDs) like receipts, medical records, and insurance forms to make decisions. Existing techniques for extracting entities from VRDs…
LEGION: Harnessing Pre-trained Language Models for GitHub Topic Recommendations with Distribution-Balance Loss
Yen-Trang Dang, Thanh-Le Cong, Phuc-Thanh Nguyen +4
Open-source development has revolutionized the software industry by promoting collaboration, transparency, and community-driven innovation. Today, a vast amount of various kinds of…
Inferring Properties of Graph Neural Networks
Dat Nguyen, Hieu M. Vu, Cong-Thanh Le +4
We propose GNNInfer, the first automatic property inference technique for GNNs. To tackle the challenge of varying input structures in GNNs, GNNInfer first identifies a set of repr…
Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing
Thanh Le-Cong, Dat Nguyen, Bach Le +1
In this paper, we propose shifting the focus of robustness evaluation for Neural Program Repair (NPR) techniques toward naturally-occurring data transformations. To accomplish this…