2 citations · 5 across the 7 of their papers we have counts for
8 papers
Decoding the Critique Mechanism in Large Reasoning Models
Hoang Phan, Quang H. Nguyen, Hung T. Q. Le +3
Large Reasoning Models (LRMs) exhibit backtracking and self-verification mechanisms that enable them to revise intermediate steps and reach correct solutions, yielding strong perfo…
Unveiling Concept Attribution in Diffusion Models
Quang H. Nguyen, Hoang Phan, Khoa D. Doan
Diffusion models have shown remarkable abilities in generating realistic and high-quality images from text prompts. However, a trained model remains largely black-box; little do we…
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
Quang H. Nguyen, Nguyen Ngoc-Hieu, The-Anh Ta +4
Deep neural networks are vulnerable to backdoor attacks, a type of adversarial attack that poisons the training data to manipulate the behavior of models trained on such data. Clea…
MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMs
Quang H. Nguyen, Thinh Dao, Duy C. Hoang +4
The rapid progress in machine learning (ML) has brought forth many large language models (LLMs) that excel in various tasks and areas. These LLMs come with different abilities and…
Synthesizing Physical Backdoor Datasets: An Automated Framework Leveraging Deep Generative Models
Sze Jue Yang, Chinh D. La, Quang H. Nguyen +4
Backdoor attacks, representing an emerging threat to the integrity of deep neural networks, have garnered significant attention due to their ability to compromise deep learning sys…
Fooling the Textual Fooler via Randomizing Latent Representations
Duy C. Hoang, Quang H. Nguyen, Saurav Manchanda +3
Despite outstanding performance in a variety of NLP tasks, recent studies have revealed that NLP models are vulnerable to adversarial attacks that slightly perturb the input to cau…