no code implementations • 23 May 2024 • Huy Nguyen, Pedram Akbarian, Trang Pham, Trang Nguyen, Shujian Zhang, Nhat Ho
The cosine router in sparse Mixture of Experts (MoE) has recently emerged as an attractive alternative to the conventional linear router.
no code implementations • 23 May 2024 • Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho
Exploiting the power of pre-trained models, prompt-based approaches stand out compared to other continual learning solutions in effectively preventing catastrophic forgetting, even with very few learnable parameters and without the need for a memory buffer.
no code implementations • 9 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.
no code implementations • 5 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.
no code implementations • 31 May 2023 • Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer
The aim of object-centric vision is to construct an explicit representation of the objects in a scene.
no code implementations • 28 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.
no code implementations • 19 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.
no code implementations • 29 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.