Zobrazeno 1 - 10
of 12 336
pro vyhledávání: '"Olatunji, SO"'
Model-based geostatistics (MBG) is a subfield of spatial statistics focused on predicting spatially continuous phenomena using data collected at discrete locations. Geostatistical models often rely on the assumptions of stationarity and isotropy for
Externí odkaz:
http://arxiv.org/abs/2412.09225
Autor:
He, Xuehai, Wang, Shuohang, Yang, Jianwei, Wu, Xiaoxia, Wang, Yiping, Wang, Kuan, Zhan, Zheng, Ruwase, Olatunji, Shen, Yelong, Wang, Xin Eric
Recent advancements in diffusion models have shown great promise in producing high-quality video content. However, efficiently training diffusion models capable of integrating directional guidance and controllable motion intensity remains a challengi
Externí odkaz:
http://arxiv.org/abs/2412.08948
Autor:
Olatunji, Tobi, Nimo, Charles, Owodunni, Abraham, Abdullahi, Tassallah, Ayodele, Emmanuel, Sanni, Mardhiyah, Aka, Chinemelu, Omofoye, Folafunmi, Yuehgoh, Foutse, Faniran, Timothy, Dossou, Bonaventure F. P., Yekini, Moshood, Kemp, Jonas, Heller, Katherine, Omeke, Jude Chidubem, MD, Chidi Asuzu, Etori, Naome A., Ndiaye, Aimérou, Okoh, Ifeoma, Ocansey, Evans Doe, Kinara, Wendy, Best, Michael, Essa, Irfan, Moore, Stephen Edward, Fourie, Chris, Asiedu, Mercy Nyamewaa
Recent advancements in large language model(LLM) performance on medical multiple choice question (MCQ) benchmarks have stimulated interest from healthcare providers and patients globally. Particularly in low-and middle-income countries (LMICs) facing
Externí odkaz:
http://arxiv.org/abs/2411.15640
Autor:
Hanke, Vincent, Blanchard, Tom, Boenisch, Franziska, Olatunji, Iyiola Emmanuel, Backes, Michael, Dziedzic, Adam
While open Large Language Models (LLMs) have made significant progress, they still fall short of matching the performance of their closed, proprietary counterparts, making the latter attractive even for the use on highly private data. Recently, vario
Externí odkaz:
http://arxiv.org/abs/2411.05818
Given the popularity of generative AI, Large Language Models (LLMs) often consume hundreds or thousands of GPUs for parallelizing and accelerating the training process. Communication overhead becomes more pronounced when training LLMs at scale. To el
Externí odkaz:
http://arxiv.org/abs/2409.15241
Autor:
Yao, Jinghan, Jacobs, Sam Ade, Tanaka, Masahiro, Ruwase, Olatunji, Shafi, Aamir, Subramoni, Hari, Panda, Dhabaleswar K.
Large Language Models (LLMs) with long context capabilities are integral to complex tasks in natural language processing and computational biology, such as text generation and protein sequence analysis. However, training LLMs directly on extremely lo
Externí odkaz:
http://arxiv.org/abs/2408.16978
Autor:
Lian, Xinyu, Jacobs, Sam Ade, Kurilenko, Lev, Tanaka, Masahiro, Bekman, Stas, Ruwase, Olatunji, Zhang, Minjia
Existing checkpointing approaches seem ill-suited for distributed training even though hardware limitations make model parallelism, i.e., sharding model state across multiple accelerators, a requirement for model scaling. Consolidating distributed mo
Externí odkaz:
http://arxiv.org/abs/2406.18820
Model checkpoints are critical Deep Learning (DL) artifacts that enable fault tolerance for training and downstream applications, such as inference. However, writing checkpoints to persistent storage, and other I/O aspects of DL training, are mostly
Externí odkaz:
http://arxiv.org/abs/2406.13768
Autor:
Afonja, Tejumade, Olatunji, Tobi, Ogun, Sewade, Etori, Naome A., Owodunni, Abraham, Yekini, Moshood
Recent strides in automatic speech recognition (ASR) have accelerated their application in the medical domain where their performance on accented medical named entities (NE) such as drug names, diagnoses, and lab results, is largely unknown. We rigor
Externí odkaz:
http://arxiv.org/abs/2406.12387
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