no code implementations • 3 Jun 2024 • Fatemeh Shiri, Van Nguyen, Farhad Moghimifar, John Yoo, Gholamreza Haffari, Yuan-Fang Li
Large Language Models (LLMs) demonstrate significant capabilities in processing natural language data, promising efficient knowledge extraction from diverse textual sources to enhance situational awareness and support decision-making.
no code implementations • 29 Jan 2024 • Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Phung
Additionally, we propose minimizing class-aware Higher-order Moment Matching (HMM) to align the corresponding class regions on the source and target domains.
1 code implementation • 26 May 2023 • Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung
Prior studies found that vulnerabilities across different vulnerable programs may exhibit similar vulnerable scopes, implicitly forming discernible vulnerability patterns that can be learned by DL models through supervised training.
no code implementations • 4 May 2023 • Farhad Moghimifar, Fatemeh Shiri, Van Nguyen, Reza Haffari, Yuan-Fang Li
In this paper, we present a novel domain-adaptive visually-fused event detection approach that can be trained on a few labelled image-text paired data points.
no code implementations • 4 May 2023 • Fatemeh Shiri, Teresa Wang, Shirui Pan, Xiaojun Chang, Yuan-Fang Li, Reza Haffari, Van Nguyen, Shuang Yu
In order to exploit the potentially useful and rich information from such sources, it is necessary to extract not only the relevant entities and concepts but also their semantic relations, together with the uncertainty associated with the extracted knowledge (i. e., in the form of probabilistic knowledge graphs).
no code implementations • 1 May 2023 • Jason Liu, Shohreh Deldari, Hao Xue, Van Nguyen, Flora D. Salim
In the context of mobile sensing environments, various sensors on mobile devices continually generate a vast amount of data.
no code implementations • 29 Oct 2022 • Mine Kerpicci, Van Nguyen, Shuhua Zhang, Erik Visser
Model architectures such as wav2vec 2. 0 and HuBERT have been proposed to learn speech representations from audio waveforms in a self-supervised manner.
1 code implementation • 27 Sep 2022 • Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin Bonilla, Gholamreza Haffari, Dinh Phung
Interpretable machine learning seeks to understand the reasoning process of complex black-box systems that are long notorious for lack of explainability.
1 code implementation • 20 Sep 2022 • Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John Grundy, Hung Nguyen, Seyit Camtepe, Paul Quirk, Dinh Phung
In this paper we propose a novel end-to-end deep learning-based approach to identify the vulnerability-relevant code statements of a specific function.
1 code implementation • 19 Sep 2022 • Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John Grundy, Hung Nguyen, Dinh Phung
However, there are still two open and significant issues for SVD in terms of i) learning automatic representations to improve the predictive performance of SVD, and ii) tackling the scarcity of labeled vulnerabilities datasets that conventionally need laborious labeling effort by experts.
1 code implementation • 7 Jul 2022 • Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Phung
A popular attribution-based approach is to exploit local neighborhoods for learning instance-specific explainers in an additive manner.
no code implementations • 21 Mar 2022 • Fatemeh Shiri, Terry Yue Zhuo, Zhuang Li, Van Nguyen, Shirui Pan, Weiqing Wang, Reza Haffari, Yuan-Fang Li
In this paper, we investigate how to exploit paraphrasing methods for the automated generation of large-scale training datasets (in the form of paraphrased utterances and their corresponding logical forms in SQL format) and present our experimental results using real-world data in the maritime domain.
1 code implementation • 14 Oct 2021 • Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung
Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks.
no code implementations • 3 Oct 2021 • Shehzeen Hussain, Van Nguyen, Shuhua Zhang, Erik Visser
Finally, we extend our framework to perform multi-task learning by jointly optimizing the network parameters on multiple voice activated tasks using a shared transformer backbone.
Ranked #6 on Speaker Verification on VoxCeleb
no code implementations • 29 Sep 2021 • Van Nguyen, Trung Le, John C. Grundy, Dinh Phung
Software vulnerabilities existing in a program or function of computer systems have been becoming a serious and crucial concern.
no code implementations • 26 Apr 2018 • Martin Gebser, Philipp Obermeier, Thomas Otto, Torsten Schaub, Orkunt Sabuncu, Van Nguyen, Tran Cao Son
More precisely, asprilo consists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques.
no code implementations • 22 Jun 2016 • Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Phung
Acquiring labels are often costly, whereas unlabeled data are usually easy to obtain in modern machine learning applications.