Zobrazeno 1 - 10
of 7 589
pro vyhledávání: '"Le, Thanh An"'
Continual Event Detection (CED) poses a formidable challenge due to the catastrophic forgetting phenomenon, where learning new tasks (with new coming event types) hampers performance on previous ones. In this paper, we introduce a novel approach, Lif
Externí odkaz:
http://arxiv.org/abs/2410.08905
Autor:
Chou, Hong-fu, Ha, Vu Nguyen, Thiruvasagam, Prabhu, Le, Thanh-Dung, Eappen, Geoffrey, Nguyen, Ti Ti, Garces-Socarras, Luis M., Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
Earth Observation (EO) systems play a crucial role in achieving Sustainable Development Goals by collecting and analyzing vital global data through satellite networks. These systems are essential for tasks like mapping, disaster monitoring, and resou
Externí odkaz:
http://arxiv.org/abs/2409.15246
Autor:
Le, Thanh-Dung, Ha, Vu Nguyen, Nguyen, Ti Ti, Eappen, Geoffrey, Thiruvasagam, Prabhu, Garces-Socarras, Luis M., Chou, Hong-fu, Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, Chatzinotas, Symeon
Remote sensing image classification is a critical component of Earth observation (EO) systems, traditionally dominated by convolutional neural networks (CNNs) and other deep learning techniques. However, the advent of Transformer-based architectures
Externí odkaz:
http://arxiv.org/abs/2409.03901
Autor:
Nguyên, Lê Thành Dũng
You might know that the name "tree transducers" refers to various kinds of automata that compute functions on ranked trees, i.e. terms over a first-order signature. But have you ever wondered about how to remember what a macro tree transducer does? O
Externí odkaz:
http://arxiv.org/abs/2409.03169
In this paper, we aim to enhance the performance of SwiftBrush, a prominent one-step text-to-image diffusion model, to be competitive with its multi-step Stable Diffusion counterpart. Initially, we explore the quality-diversity trade-off between Swif
Externí odkaz:
http://arxiv.org/abs/2408.14176
Fine-tuning Large Language Models (LLMs) for clinical Natural Language Processing (NLP) poses significant challenges due to the domain gap and limited data availability. This study investigates the effectiveness of various adapter techniques, equival
Externí odkaz:
http://arxiv.org/abs/2407.19299
Remote patient monitoring has emerged as a prominent non-invasive method, using digital technologies and computer vision (CV) to replace traditional invasive monitoring. While neonatal and pediatric departments embrace this approach, Pediatric Intens
Externí odkaz:
http://arxiv.org/abs/2407.13341
Autor:
Luong, Tinh Son, Le, Thanh-Thien, Doan, Thang Viet, Van, Linh Ngo, Nguyen, Thien Huu, Nguyen, Diep Thi-Ngoc
Existing toxic detection models face significant limitations, such as lack of transparency, customization, and reproducibility. These challenges stem from the closed-source nature of their training data and the paucity of explanations for their evalu
Externí odkaz:
http://arxiv.org/abs/2406.14835
Autor:
Lompo, Boammani Aser, Le, Thanh-Dung
This research aims to classify numerical values extracted from medical documents across seven distinct physiological categories, employing CamemBERT-bio. Previous studies suggested that transformer-based models might not perform as well as traditiona
Externí odkaz:
http://arxiv.org/abs/2405.18448
Autor:
Le, Thanh-Dung
This study delves into the effectiveness of various learning methods in improving Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN-Transformer) in the context of pediatric intensive care units (PICU) with limit
Externí odkaz:
http://arxiv.org/abs/2405.16177