Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Nguyen Tuan Dung"'
Autor:
de Haan, Tijmen, Ting, Yuan-Sen, Ghosal, Tirthankar, Nguyen, Tuan Dung, Accomazzi, Alberto, Wells, Azton, Ramachandra, Nesar, Pan, Rui, Sun, Zechang
AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, and cosmology. Trained on the complete collection of astronomy-related arXiv papers from 2007-2024 along with millions of s
Externí odkaz:
http://arxiv.org/abs/2411.09012
Autor:
Pan, Rui, Nguyen, Tuan Dung, Arora, Hardik, Accomazzi, Alberto, Ghosal, Tirthankar, Ting, Yuan-Sen
Continual pretraining of large language models on domain-specific data has been proposed to enhance performance on downstream tasks. In astronomy, the previous absence of astronomy-focused benchmarks has hindered objective evaluation of these special
Externí odkaz:
http://arxiv.org/abs/2409.19750
Autor:
Ting, Yuan-Sen, Nguyen, Tuan Dung, Ghosal, Tirthankar, Pan, Rui, Arora, Hardik, Sun, Zechang, de Haan, Tijmen, Ramachandra, Nesar, Wells, Azton, Madireddy, Sandeep, Accomazzi, Alberto
We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy an
Externí odkaz:
http://arxiv.org/abs/2407.11194
Autor:
Nguyen, Tung-Anh, Le, Long Tan, Nguyen, Tuan Dung, Bao, Wei, Seneviratne, Suranga, Hong, Choong Seon, Tran, Nguyen H.
Publikováno v:
IEEE/ACM Transactions on Networking On page(s): 1-16 Print ISSN: 1063-6692 Online ISSN: 1558-2566 Digital Object Identifier: 10.1109/TNET.2024.3423780
With the proliferation of the Internet of Things (IoT) and the rising interconnectedness of devices, network security faces significant challenges, especially from anomalous activities. While traditional machine learning-based intrusion detection sys
Externí odkaz:
http://arxiv.org/abs/2407.07421
Autor:
Shen, Yulin, Primeau, Louis, Li, Jiangxu, Nguyen, Tuan-Dung, Mandrus, David, Lin, Yuxuan Cosmi, Zhang, Yang
Unlocking the vast potential of optical sensing technology has long been hindered by the challenges of achieving fast, sensitive, and broadband photodetection at ambient temperatures. In this review, we summarize recent progress in the study of nonli
Externí odkaz:
http://arxiv.org/abs/2406.11982
Autor:
Perkowski, Ernest, Pan, Rui, Nguyen, Tuan Dung, Ting, Yuan-Sen, Kruk, Sandor, Zhang, Tong, O'Neill, Charlie, Jablonska, Maja, Sun, Zechang, Smith, Michael J., Liu, Huiling, Schawinski, Kevin, Iyer, Kartheik, UniverseTBD, Ioana Ciucă for
We explore the potential of enhancing LLM performance in astronomy-focused question-answering through targeted, continual pre-training. By employing a compact 7B-parameter LLaMA-2 model and focusing exclusively on a curated set of astronomy corpora -
Externí odkaz:
http://arxiv.org/abs/2401.01916
Autor:
Nguyen, Anh Duc, Nguyen, Tuan Dung, Nguyen, Quang Minh, Nguyen, Hoang H., Nguyen, Lam M., Toh, Kim-Chuan
This paper studies the Partial Optimal Transport (POT) problem between two unbalanced measures with at most $n$ supports and its applications in various AI tasks such as color transfer or domain adaptation. There is hence the need for fast approximat
Externí odkaz:
http://arxiv.org/abs/2312.13970
Autor:
Nguyen, Tuan Dung, Chen, Ziyu, Carroll, Nicholas George, Tran, Alasdair, Klein, Colin, Xie, Lexing
The ever-growing textual records of contemporary social issues, often discussed online with moral rhetoric, present both an opportunity and a challenge for studying how moral concerns are debated in real life. Moral foundations theory is a taxonomy o
Externí odkaz:
http://arxiv.org/abs/2311.10219
Autor:
Le, Long Tan, Nguyen, Tuan Dung, Nguyen, Tung-Anh, Hong, Choong Seon, Seneviratne, Suranga, Bao, Wei, Tran, Nguyen H.
Federated Learning (FL) has emerged as a groundbreaking distributed learning paradigm enabling clients to train a global model collaboratively without exchanging data. Despite enhancing privacy and efficiency in information retrieval and knowledge ma
Externí odkaz:
http://arxiv.org/abs/2309.15659
Autor:
Nguyen, Tuan Dung, Ting, Yuan-Sen, Ciucă, Ioana, O'Neill, Charlie, Sun, Ze-Chang, Jabłońska, Maja, Kruk, Sandor, Perkowski, Ernest, Miller, Jack, Li, Jason, Peek, Josh, Iyer, Kartheik, Różański, Tomasz, Khetarpal, Pranav, Zaman, Sharaf, Brodrick, David, Méndez, Sergio J. Rodríguez, Bui, Thang, Goodman, Alyssa, Accomazzi, Alberto, Naiman, Jill, Cranney, Jesse, Schawinski, Kevin, UniverseTBD
Large language models excel in many human-language tasks but often falter in highly specialized domains like scholarly astronomy. To bridge this gap, we introduce AstroLLaMA, a 7-billion-parameter model fine-tuned from LLaMA-2 using over 300,000 astr
Externí odkaz:
http://arxiv.org/abs/2309.06126