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Zahid Masood, Muhammad Usama, Shahroz Khan, Konstantinos Kostas and Panagiotis D. Kaklis
Generative models offer design diversity but tend to be computationally expensive, while non-generative models are computationally cost-effective but produce less diverse and often invalid designs. However, the limitations of non-generative models can be...
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Nguyen Trung Tuan, Philip Moore, Dat Ha Vu Thanh and Hai Van Pham
ChatGPT plays significant roles in the third decade of the 21st Century. Smart cities applications can be integrated with ChatGPT in various fields. This research proposes an approach for developing large language models using generative artificial intel...
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Navid Khalili Dizaji and Mustafa Dogan
Brain tumors are one of the deadliest types of cancer. Rapid and accurate identification of brain tumors, followed by appropriate surgical intervention or chemotherapy, increases the probability of survival. Accurate determination of brain tumors in MRI ...
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Minh-Quan Vo, Thu Nguyen, Michael A. Riegler and Hugo L. Hammer
Generative models have recently received a lot of attention. However, a challenge with such models is that it is usually not possible to compute the likelihood function, which makes parameter estimation or training of the models challenging. The most com...
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Lucas Lopes Oliveira, Xiaorui Jiang, Aryalakshmi Nellippillipathil Babu, Poonam Karajagi and Alireza Daneshkhah
Early identification of acute gout is crucial, enabling healthcare professionals to implement targeted interventions for rapid pain relief and preventing disease progression, ensuring improved long-term joint function. In this study, we comprehensively e...
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Kara Combs, Adam Moyer and Trevor J. Bihl
Recently, generative artificial intelligence (GAI) has impressed the world with its ability to create text, images, and videos. However, there are still areas in which GAI produces undesirable or unintended results due to being ?uncertain?. Before wider ...
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Weiying Wang and Toshihiro Osaragi
The generation and prediction of daily human mobility patterns have raised significant interest in many scientific disciplines. Using various data sources, previous studies have examined several deep learning frameworks, such as the RNN and GAN, to synth...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Zhe Yang, Yi Huang, Yaqin Chen, Xiaoting Wu, Junlan Feng and Chao Deng
Controllable Text Generation (CTG) aims to modify the output of a Language Model (LM) to meet specific constraints. For example, in a customer service conversation, responses from the agent should ideally be soothing and address the user?s dissatisfactio...
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Ioana Branescu, Octavian Grigorescu and Mihai Dascalu
Effectively understanding and categorizing vulnerabilities is vital in the ever-evolving cybersecurity landscape, since only one exposure can have a devastating effect on the entire system. Given the increasingly massive number of threats and the size of...
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