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of 6 461
pro vyhledávání: '"Myat TO"'
Recent studies reveal that Large Language Models (LLMs) are susceptible to backdoor attacks, where adversaries embed hidden triggers that manipulate model responses. Existing backdoor defense methods are primarily designed for vision or classificatio
Externí odkaz:
http://arxiv.org/abs/2411.12768
Autor:
Kyaw, Kaung Myat, Chan, Jonathan Hoyin
In this paper, we introduce ConversaSynth, a framework designed to generate synthetic conversation audio using large language models (LLMs) with multiple persona settings. The framework first creates diverse and coherent text-based dialogues across v
Externí odkaz:
http://arxiv.org/abs/2409.00946
Autor:
Wang, Huichen Will, Hoffswell, Jane, Thane, Sao Myat Thazin, Bursztyn, Victor S., Bearfield, Cindy Xiong
Large Language Models (LLMs) have been adopted for a variety of visualizations tasks, but how far are we from perceptually aware LLMs that can predict human takeaways? Graphical perception literature has shown that human chart takeaways are sensitive
Externí odkaz:
http://arxiv.org/abs/2408.06837
The application of deep neural network models in various security-critical applications has raised significant security concerns, particularly the risk of backdoor attacks. Neural backdoors pose a serious security threat as they allow attackers to ma
Externí odkaz:
http://arxiv.org/abs/2405.14781
Publikováno v:
Engineering, Construction and Architectural Management, 2023, Vol. 31, Issue 10, pp. 4001-4015.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ECAM-11-2022-1099
Autor:
Sankar, Ramanakumar, Mantha, Kameswara, Fortson, Lucy, Spiers, Helen, Pengo, Thomas, Mashek, Douglas, Mo, Myat, Sanders, Mark, Christensen, Trace, Salisbury, Jeffrey, Trouille, Laura
In the era of big data in scientific research, there is a necessity to leverage techniques which reduce human effort in labeling and categorizing large datasets by involving sophisticated machine tools. To combat this problem, we present a novel, gen
Externí odkaz:
http://arxiv.org/abs/2311.14177
This paper reports our submission under the team name `SynthDetectives' to the ALTA 2023 Shared Task. We use a stacking ensemble of Transformers for the task of AI-generated text detection. Our approach is novel in terms of its choice of models in th
Externí odkaz:
http://arxiv.org/abs/2310.18906
Autor:
Ratana Charoenpanyakul, Veerayuth Kittichai, Songpol Eiamsamang, Patchara Sriwichai, Natchapon Pinetsuksai, Kaung Myat Naing, Teerawat Tongloy, Siridech Boonsang, Santhad Chuwongin
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract Traditional mosquito identification methods, relied on microscopic observation and morphological characteristics, often require significant expertise and experience, which can limit their effectiveness. This study introduces a self-supervise
Externí odkaz:
https://doaj.org/article/180b062b2a844c6ebe77d702b92a1eee
Publikováno v:
Infectious Diseases of Poverty, Vol 13, Iss 1, Pp 1-13 (2024)
Abstract Background The financial burden of tuberculosis (TB) can hinder patients and their families, creating obstacles throughout the care cascade, despite TB prevention and control being provided free of charge. In Myanmar, patients can visit priv
Externí odkaz:
https://doaj.org/article/3e5bacd64436482fb275b38524aec308
Autor:
Qiang Xu, Takeshi Nabeshima, Koichiro Hamada, Takashi Sugimoto, Mya Myat Ngwe Tun, Kouichi Morita, Hirotomo Yamanashi, Takahiro Maeda, Koya Ariyoshi, Yuki Takamatsu
Publikováno v:
Emerging Infectious Diseases, Vol 30, Iss 11, Pp 2419-2423 (2024)
We report a human case of severe fever with thrombocytopenia syndrome virus infection transmitted by a tick, confirmed by viral identification. Haemaphysalis aborensis, a tick species not native to Japan that has been observed to transmit the virus t
Externí odkaz:
https://doaj.org/article/821782939d0949fc853ba58f3938d808