Zobrazeno 1 - 10
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pro vyhledávání: '"A, Mars"'
Understanding the nature of dark matter in the Universe is an important goal of modern cosmology. A key method for probing this distribution is via weak gravitational lensing mass-mapping - a challenging ill-posed inverse problem where one infers the
Externí odkaz:
http://arxiv.org/abs/2410.24197
The recent emergence of Large Language Models (LLMs) has heralded a new era of human-AI interaction. These sophisticated models, exemplified by Chat-GPT and its successors, have exhibited remarkable capabilities in language understanding. However, as
Externí odkaz:
http://arxiv.org/abs/2407.18078
We prove two results which are relevant for constructing marginally outer trapped tubes (MOTTs) in de Sitter spacetime. The first one holds more generally, namely for spacetimes satisfying the null convergence condition and containing a timelike conf
Externí odkaz:
http://arxiv.org/abs/2407.10602
Autor:
Daynauth, Roland, Mars, Jason
The SLAM paper demonstrated that on-device Small Language Models (SLMs) are a viable and cost-effective alternative to API-based Large Language Models (LLMs), such as OpenAI's GPT-4, offering comparable performance and stability. However, SLAM also i
Externí odkaz:
http://arxiv.org/abs/2407.12847
Understanding the large-scale structure of the Universe and unravelling the mysteries of dark matter are fundamental challenges in contemporary cosmology. Reconstruction of the cosmological matter distribution from lensing observables, referred to as
Externí odkaz:
http://arxiv.org/abs/2406.15424
Autor:
Mars, Jason, Kang, Yiping, Dantanarayana, Jayanaka L., Irugalbandara, Chandra, Sivasothynathan, Kugesan, Clarke, Christopher, Li, Baichuan, Tang, Lingjia
Programming with Generative AI (GenAI) models, which frequently involves using large language models (LLMs) to accomplish specific functionalities, has experienced significant growth in adoption. However, it remains a complex process, as developers o
Externí odkaz:
http://arxiv.org/abs/2405.08965
With the next generation of interferometric telescopes, such as the Square Kilometre Array (SKA), the need for highly computationally efficient reconstruction techniques is particularly acute. The challenge in designing learned, data-driven reconstru
Externí odkaz:
http://arxiv.org/abs/2405.08958
Autor:
Mars, Marc, Sánchez-Pérez, Gabriel
This is the first in a series of two papers where we analyze the transverse expansion of the metric on a general null hypersurface. In this paper we obtain general geometric identities relating the transverse derivatives of the ambient Ricci tensor a
Externí odkaz:
http://arxiv.org/abs/2405.05377
While major languages often enjoy substantial attention and resources, the linguistic diversity across the globe encompasses a multitude of smaller, indigenous, and regional languages that lack the same level of computational support. One such region
Externí odkaz:
http://arxiv.org/abs/2405.03832
Autor:
Jung, Raehyuk, Go, Hyojun, Yi, Jaehyuk, Jang, Jiho, Kim, Daniel, Suh, Jay, Lee, Aiden, Han, Cooper, Lee, Jae, Kim, Jeff, Kim, Jin-Young, Kim, Junwan, Park, Kyle, Lee, Lucas, Ha, Mars, Seo, Minjoon, Jo, Abraham, Park, Ed, Kianinejad, Hassan, Kim, SJ, Moon, Tony, Jeong, Wade, Popescu, Andrei, Kim, Esther, Yoon, EK, Heo, Genie, Choi, Henry, Kang, Jenna, Han, Kevin, Seo, Noah, Nguyen, Sunny, Won, Ryan, Park, Yeonhoo, Giuliani, Anthony, Chung, Dave, Yoon, Hans, Le, James, Ahn, Jenny, Lee, June, Saini, Maninder, Sanders, Meredith, Lee, Soyoung, Kim, Sue, Couture, Travis
This technical report introduces Pegasus-1, a multimodal language model specialized in video content understanding and interaction through natural language. Pegasus-1 is designed to address the unique challenges posed by video data, such as interpret
Externí odkaz:
http://arxiv.org/abs/2404.14687