no code implementations • 28 Oct 2022 • Chuqin Geng, Nham Le, Xiaojie Xu, Zhaoyue Wang, Arie Gurfinkel, Xujie Si
We show that by using NAP, we can verify a significant region of the input space, while still recalling 84% of the data on MNIST.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Nham Le, Tuan Lai, Trung Bui, Doo Soon Kim
With the renaissance of deep learning, neural networks have achieved promising results on many natural language understanding (NLU) tasks.
no code implementations • COLING 2020 • Quan Tran, Nhan Dam, Tuan Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung
Interpretability and explainability of deep neural networks are challenging due to their scale, complexity, and the agreeable notions on which the explaining process rests.
no code implementations • 3 Dec 2018 • Jacqueline Brixey, Ramesh Manuvinakurike, Nham Le, Tuan Lai, Walter Chang, Trung Bui
This work presents the task of modifying images in an image editing program using natural language written commands.