no code implementations • 27 Aug 2023 • Thanh Duc Hoang, Do Viet Tung, Duy-Hung Nguyen, Bao-Sinh Nguyen, Huy Hoang Nguyen, Hung Le
We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution.
no code implementations • 26 Sep 2022 • Bao-Sinh Nguyen, Dung Tien Le, Hieu M. Vu, Tuan Anh D. Nguyen, Minh-Tien Nguyen, Hung Le
In this paper, we investigate the problem of improving the performance of Artificial Intelligence systems in understanding document images, especially in cases where training data is limited.
no code implementations • 1 Jun 2022 • Bao-Sinh Nguyen, Quang-Bach Tran, Tuan-Anh Nguyen Dang, Duc Nguyen, Hung Le
Measuring the confidence of AI models is critical for safely deploying AI in real-world industrial systems.
no code implementations • Findings (NAACL) 2022 • Duy-Hung Nguyen, Nguyen Viet Dung Nghiem, Bao-Sinh Nguyen, Dung Tien Le, Shahab Sabahi, Minh-Tien Nguyen, Hung Le
For summarization, human preference is critical to tame outputs of the summarizer in favor of human interests, as ground-truth summaries are scarce and ambiguous.
no code implementations • 13 Nov 2021 • Duy-Hung Nguyen, Bao-Sinh Nguyen, Nguyen Viet Dung Nghiem, Dung Tien Le, Mim Amina Khatun, Minh-Tien Nguyen, Hung Le
Automatic summarization of legal texts is an important and still a challenging task since legal documents are often long and complicated with unusual structures and styles.