Zobrazeno 1 - 10
of 20 945
pro vyhledávání: '"A, Dahan"'
Autor:
Dahan, Elay, Indelman, Hedda Cohen, Perez-Agosto, Angeles M., Shiran, Carmit, Avinash, Gopal, Shaked, Doron, Daniel, Nati
The use of synthetic images in medical imaging Artificial Intelligence (AI) solutions has been shown to be beneficial in addressing the limited availability of diverse, unbiased, and representative data. Despite the extensive use of synthetic image g
Externí odkaz:
http://arxiv.org/abs/2412.05833
Oracle character recognition-an analysis of ancient Chinese inscriptions found on oracle bones-has become a pivotal field intersecting archaeology, paleography, and historical cultural studies. Traditional methods of oracle character recognition have
Externí odkaz:
http://arxiv.org/abs/2411.11354
Autor:
Dahan, Noam, Stanovsky, Gabriel
Automatic summarization has consistently attracted attention, due to its versatility and wide application in various downstream tasks. Despite its popularity, we find that annotation efforts have largely been disjointed, and have lacked common termin
Externí odkaz:
http://arxiv.org/abs/2411.04585
Misinformation, defined as false or inaccurate information, can result in significant societal harm when it is spread with malicious or even innocuous intent. The rapid online information exchange necessitates advanced detection mechanisms to mitigat
Externí odkaz:
http://arxiv.org/abs/2410.03829
Generative AI models, such as the GPT and Llama series, have significant potential to assist laypeople in answering legal questions. However, little prior work focuses on the data sourcing, inference, and evaluation of these models in the context of
Externí odkaz:
http://arxiv.org/abs/2409.07713
This study focuses on relay transport carriers (RTCs) that contract with hub providers to lease hub capacity and employ relay transportation via hubs. It enables long-haul freight shipments to be transported by multiple short-haul drivers commuting b
Externí odkaz:
http://arxiv.org/abs/2406.16010
Autor:
Munroe, Lindsay, da Silva, Mariana, Heidari, Faezeh, Grigorescu, Irina, Dahan, Simon, Robinson, Emma C., Deprez, Maria, So, Po-Wah
Clinical adoption of deep learning models has been hindered, in part, because the black-box nature of neural networks leads to concerns regarding their trustworthiness and reliability. These concerns are particularly relevant in the field of neuroima
Externí odkaz:
http://arxiv.org/abs/2406.17792
Autor:
Dahan, Tehila, Levy, Kfir Y.
In this paper, we investigate the challenging framework of Byzantine-robust training in distributed machine learning (ML) systems, focusing on enhancing both efficiency and practicality. As distributed ML systems become integral for complex ML tasks,
Externí odkaz:
http://arxiv.org/abs/2405.14759
Autor:
Indelman, Hedda Cohen, Dahan, Elay, Perez-Agosto, Angeles M., Shiran, Carmit, Shaked, Doron, Daniel, Nati
Despite the remarkable success of deep learning in medical imaging analysis, medical image segmentation remains challenging due to the scarcity of high-quality labeled images for supervision. Further, the significant domain gap between natural and me
Externí odkaz:
http://arxiv.org/abs/2404.16325
This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It suggests leveraging foundational models enhanced by domain-specific kno
Externí odkaz:
http://arxiv.org/abs/2404.12349