Zobrazeno 1 - 10
of 24 391
pro vyhledávání: '"Ojo AS"'
Autor:
Tonja, Atnafu Lambebo, Dossou, Bonaventure F. P., Ojo, Jessica, Rajab, Jenalea, Thior, Fadel, Wairagala, Eric Peter, Aremu, Anuoluwapo, Moiloa, Pelonomi, Abbott, Jade, Marivate, Vukosi, Rosman, Benjamin
High-resource language models often fall short in the African context, where there is a critical need for models that are efficient, accessible, and locally relevant, even amidst significant computing and data constraints. This paper introduces Inkub
Externí odkaz:
http://arxiv.org/abs/2408.17024
Autor:
Simon, Emmanuel Iko-Ojo, Hettiarachchi, Chirath, Potanin, Alex, Suominen, Hanna, Fard, Fatemeh
Context: Previous studies demonstrate that Machine or Deep Learning (ML/DL) models can detect Technical Debt from source code comments called Self-Admitted Technical Debt (SATD). Despite the importance of ML/DL in software development, limited studie
Externí odkaz:
http://arxiv.org/abs/2408.10529
Autor:
Adelani, David Ifeoluwa, Ojo, Jessica, Azime, Israel Abebe, Zhuang, Jian Yun, Alabi, Jesujoba O., He, Xuanli, Ochieng, Millicent, Hooker, Sara, Bukula, Andiswa, Lee, En-Shiun Annie, Chukwuneke, Chiamaka, Buzaaba, Happy, Sibanda, Blessing, Kalipe, Godson, Mukiibi, Jonathan, Kabongo, Salomon, Yuehgoh, Foutse, Setaka, Mmasibidi, Ndolela, Lolwethu, Odu, Nkiruka, Mabuya, Rooweither, Muhammad, Shamsuddeen Hassan, Osei, Salomey, Samb, Sokhar, Guge, Tadesse Kebede, Stenetorp, Pontus
Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (e.g. African languages) are often evaluated only on basic text
Externí odkaz:
http://arxiv.org/abs/2406.03368
Autor:
Oyeyemi, Dare Azeez, Ojo, Adebola K.
Publikováno v:
Volume 38, Issue 10, Page 144-156, 2023; Article no.JAMCS.108409 ISSN: 2456-9968
In the modern era, mobile phones have become ubiquitous, and Short Message Service (SMS) has grown to become a multi-million-dollar service due to the widespread adoption of mobile devices and the millions of people who use SMS daily. However, SMS sp
Externí odkaz:
http://arxiv.org/abs/2406.06578
Autor:
Acharya, Sudip, Stanchu, Hryhorii, Kumar, Rajesh, Ojo, Solomon, Benamara, Mourad, Chang, Guo-En, Li, Baohua, Du, Wei, Yu, Shui-Qing
Owing to its true direct bandgap and tunable bandgap energies,GeSn alloys are increasingly attractive as gain media for mid-IR lasers that can be monolithically integrated on Si. Demonstrations of optically pumped GeSn laser at room under pulsed cond
Externí odkaz:
http://arxiv.org/abs/2405.10163
Monolayers of ReS2 were grown by a chemical vapor deposition technique on SiO2/Si substrates and investigated at room temperature by using micro-Raman, micro-photoluminescence (PL) and absorbance spectroscopies. The Raman scattering spectrum exhibits
Externí odkaz:
http://arxiv.org/abs/2404.13241
Optical Communication in Free Space (FSO) bids more radio bandwidth, operates under a gratis license, and has a lower startup cost as compared to Radio Frequency (RF). Nonetheless, its vulnerability to variations in atmospheric meteorological circums
Externí odkaz:
http://arxiv.org/abs/2403.15461
Autor:
Ojo, Olumide Ebenezer, Adebanji, Olaronke Oluwayemisi, Gelbukh, Alexander, Calvo, Hiram, Feldman, Anna
Effective communication between healthcare providers and patients is crucial to providing high-quality patient care. In this work, we investigate how Doctor-written and AI-generated texts in healthcare consultations can be classified using state-of-t
Externí odkaz:
http://arxiv.org/abs/2402.04442
Autor:
Lee, Patrick, Trujillo, Alain Chirino, Plancarte, Diana Cuevas, Ojo, Olumide Ebenezer, Liu, Xinyi, Shode, Iyanuoluwa, Zhao, Yuan, Peng, Jing, Feldman, Anna
This study investigates the computational processing of euphemisms, a universal linguistic phenomenon, across multiple languages. We train a multilingual transformer model (XLM-RoBERTa) to disambiguate potentially euphemistic terms (PETs) in multilin
Externí odkaz:
http://arxiv.org/abs/2401.14526
Autor:
Ojo, Olumide E., Adebanji, Olaronke O., Calvo, Hiram, Dieke, Damian O., Ojo, Olumuyiwa E., Akinsanya, Seye E., Abiola, Tolulope O., Feldman, Anna
In this paper, we share our best performing submission to the Arabic AI Tasks Evaluation Challenge (ArAIEval) at ArabicNLP 2023. Our focus was on Task 1, which involves identifying persuasion techniques in excerpts from tweets and news articles. The
Externí odkaz:
http://arxiv.org/abs/2310.09661