Search Results for author: Trang Nguyen

Found 14 papers, 2 papers with code

Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification

no code implementations24 Mar 2025 Kenneth Alperin, Rohan Leekha, Adaku Uchendu, Trang Nguyen, Srilakshmi Medarametla, Carlos Levya Capote, Seth Aycock, Charlie Dagli

Thus, we perturb an accurate authorship verification model, and achieve maximum attack success rates of 92\% and 78\% for both obfuscation and impersonation attacks, respectively.

Adversarial Robustness Authorship Verification

A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors

1 code implementation3 Feb 2025 Minh Ngoc Nguyen, Khai Le-Duc, Tan-Hanh Pham, Trang Nguyen, Quang Minh Luu, Ba Kien Tran, Truong-Son Hy, Viktor Dremin, Sergei Sokolovsky, Edik Rafailov

In this study, we introduce a novel method to predict mental health by building machine learning models for a non-invasive wearable device equipped with Laser Doppler Flowmetry (LDF) and Fluorescence Spectroscopy (FS) sensors.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Adaptive Prompting for Continual Relation Extraction: A Within-Task Variance Perspective

no code implementations11 Dec 2024 Minh Le, Tien Ngoc Luu, An Nguyen The, Thanh-Thien Le, Trang Nguyen, Tung Thanh Nguyen, Linh Ngo Van, Thien Huu Nguyen

To address catastrophic forgetting in Continual Relation Extraction (CRE), many current approaches rely on memory buffers to rehearse previously learned knowledge while acquiring new tasks.

Continual Relation Extraction Mixture-of-Experts +1

Attack On Prompt: Backdoor Attack in Prompt-Based Continual Learning

no code implementations28 Jun 2024 Trang Nguyen, Anh Tran, Nhat Ho

Prompt-based approaches offer a cutting-edge solution to data privacy issues in continual learning, particularly in scenarios involving multiple data suppliers where long-term storage of private user data is prohibited.

Backdoor Attack Continual Learning +1

Mixture of Experts Meets Prompt-Based Continual Learning

1 code implementation23 May 2024 Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho

While existing prompt-based continual learning methods excel in leveraging prompts for state-of-the-art performance, they often lack a theoretical explanation for the effectiveness of prompting.

Continual Learning Mixture-of-Experts

Statistical Advantages of Perturbing Cosine Router in Mixture of Experts

no code implementations23 May 2024 Huy Nguyen, Pedram Akbarian, Trang Pham, Trang Nguyen, Shujian Zhang, Nhat Ho

The cosine router in Mixture of Experts (MoE) has recently emerged as an attractive alternative to the conventional linear router.

Mixture-of-Experts

Causal Reasoning through Two Layers of Cognition for Improving Generalization in Visual Question Answering

no code implementations9 Oct 2023 Trang Nguyen, Naoaki Okazaki

Besides, diverse interpretations of the input lead to various modes of answer generation, highlighting the role of causal reasoning between interpreting and answering steps in VQA.

Answer Generation Question Answering +1

Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems

no code implementations5 Oct 2023 Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu

Understanding causal relationships within Gene Regulatory Networks (GRNs) is essential for unraveling the gene interactions in cellular processes.

Causal Discovery Causal Inference

The 2022 NIST Language Recognition Evaluation

no code implementations28 Feb 2023 Yooyoung Lee, Craig Greenberg, Eliot Godard, Asad A. Butt, Elliot Singer, Trang Nguyen, Lisa Mason, Douglas Reynolds

In 2022, the U. S. National Institute of Standards and Technology (NIST) conducted the latest Language Recognition Evaluation (LRE) in an ongoing series administered by NIST since 1996 to foster research in language recognition and to measure state-of-the-art technology.

valid

Fast Approximation of the Generalized Sliced-Wasserstein Distance

no code implementations19 Oct 2022 Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho

Generalized sliced Wasserstein distance is a variant of sliced Wasserstein distance that exploits the power of non-linear projection through a given defining function to better capture the complex structures of the probability distributions.

On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks

no code implementations29 Oct 2021 Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho

To address this issue, we propose a novel model fusion framework, named CLAFusion, to fuse neural networks with a different number of layers, which we refer to as heterogeneous neural networks, via cross-layer alignment.

Knowledge Distillation Model Compression

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