Zobrazeno 1 - 10
of 5 373
pro vyhledávání: '"Tosin, A."'
Autor:
Ige, Tosin, Kiekintveld, Christopher, Piplai, Aritran, Waggler, Amy, Kolade, Olukunle, Matti, Bolanle Hafiz
Phishing is one of the most effective ways in which cybercriminals get sensitive details such as credentials for online banking, digital wallets, state secrets, and many more from potential victims. They do this by spamming users with malicious URLs
Externí odkaz:
http://arxiv.org/abs/2411.16751
We introduce a counting process to model the random occurrence in time of car traffic accidents, taking into account some aspects of the self-excitation typical of this phenomenon. By combining methods from probability and differential equations, we
Externí odkaz:
http://arxiv.org/abs/2410.00446
Autor:
Lima, Keila, Nguyen, Ngoc-Thanh, Heldal, Rogardt, Kristensen, Lars Michael, Oyetoyan, Tosin Daniel, Pelliccione, Patrizio, Knauss, Eric
Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of marine ecosys
Externí odkaz:
http://arxiv.org/abs/2407.13231
The importance of addressing fairness and bias in artificial intelligence (AI) systems cannot be over-emphasized. Mainstream media has been awashed with news of incidents around stereotypes and other types of bias in many of these systems in recent y
Externí odkaz:
http://arxiv.org/abs/2406.19097
Autor:
Ogun, Sewade, Owodunni, Abraham T., Olatunji, Tobi, Alese, Eniola, Oladimeji, Babatunde, Afonja, Tejumade, Olaleye, Kayode, Etori, Naome A., Adewumi, Tosin
Recent advances in speech synthesis have enabled many useful applications like audio directions in Google Maps, screen readers, and automated content generation on platforms like TikTok. However, these systems are mostly dominated by voices sourced f
Externí odkaz:
http://arxiv.org/abs/2406.11727
Autor:
Pagliai, Irene, van Boven, Goya, Adewumi, Tosin, Alkhaled, Lama, Gurung, Namrata, Södergren, Isabella, Barney, Elisa
We introduce new large labeled datasets on bias in 3 languages and show in experiments that bias exists in all 10 datasets of 5 languages evaluated, including benchmark datasets on the English GLUE/SuperGLUE leaderboards. The 3 new languages give a t
Externí odkaz:
http://arxiv.org/abs/2404.04838
In this work, we provide insight into one important limitation of large language models (LLMs), i.e. false attribution, and introduce a new hallucination metric - Simple Hallucination Index (SHI). The task of automatic author attribution for relative
Externí odkaz:
http://arxiv.org/abs/2404.04631
We present insightful results of a survey on the adoption of generative artificial intelligence (GenAI) by university teachers in their teaching activities. The transformation of education by GenAI, particularly large language models (LLMs), has been
Externí odkaz:
http://arxiv.org/abs/2404.03486
Autor:
Nakamura, Taishi, Mishra, Mayank, Tedeschi, Simone, Chai, Yekun, Stillerman, Jason T, Friedrich, Felix, Yadav, Prateek, Laud, Tanmay, Chien, Vu Minh, Zhuo, Terry Yue, Misra, Diganta, Bogin, Ben, Vu, Xuan-Son, Karpinska, Marzena, Dantuluri, Arnav Varma, Kusa, Wojciech, Furlanello, Tommaso, Yokota, Rio, Muennighoff, Niklas, Pai, Suhas, Adewumi, Tosin, Laippala, Veronika, Yao, Xiaozhe, Junior, Adalberto, Ariyak, Alpay, Drozd, Aleksandr, Clive, Jordan, Gupta, Kshitij, Chen, Liangyu, Sun, Qi, Tsui, Ken, Persaud, Noah, Fahmy, Nour, Chen, Tianlong, Bansal, Mohit, Monti, Nicolo, Dang, Tai, Luo, Ziyang, Bui, Tien-Tung, Navigli, Roberto, Mehta, Virendra, Blumberg, Matthew, May, Victor, Nguyen, Huu, Pyysalo, Sampo
Pretrained language models underpin several AI applications, but their high computational cost for training limits accessibility. Initiatives such as BLOOM and StarCoder aim to democratize access to pretrained models for collaborative community devel
Externí odkaz:
http://arxiv.org/abs/2404.00399
The ever-evolving ways attacker continues to im prove their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of
Externí odkaz:
http://arxiv.org/abs/2402.17249