94 citations · 120 across the 6 of their papers we have counts for
7 papers
ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation
Long Phan, Hieu Tran, Hieu Nguyen +1
We present ViT5, a pretrained Transformer-based encoder-decoder model for the Vietnamese language. With T5-style self-supervised pretraining, ViT5 is trained on a large corpus of h…
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations
Nathan Beck, Abhiramon Rajasekharan, Hieu Tran
Transfer learning approaches in reinforcement learning aim to assist agents in learning their target domains by leveraging the knowledge learned from other agents that have been tr…
VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization?
Hieu Nguyen, Long Phan, James Anibal +2
Text summarization is a challenging task within natural language processing that involves text generation from lengthy input sequences. While this task has been widely studied in E…
CoTexT: Multi-task Learning with Code-Text Transformer
Long Phan, Hieu Tran, Daniel Le +4
We present CoTexT, a pre-trained, transformer-based encoder-decoder model that learns the representative context between natural language (NL) and programming language (PL). Using…
SciFive: a text-to-text transformer model for biomedical literature
Long N. Phan, James T. Anibal, Hieu Tran +4
In this report, we introduce SciFive, a domain-specific T5 model that has been pre-trained on large biomedical corpora. Our model outperforms the current SOTA methods (i.e. BERT, B…
Hierarchical Transformer Encoders for Vietnamese Spelling Correction
Hieu Tran, Cuong V. Dinh, Long Phan +1
In this paper, we propose a Hierarchical Transformer model for Vietnamese spelling correction problem. The model consists of multiple Transformer encoders and utilizes both charact…