Zobrazeno 1 - 10
of 79 646
pro vyhledávání: '"Wins P"'
Autor:
Cheng, Chun-Wun, Huang, Jiahao, Zhang, Yi, Yang, Guang, Schönlieb, Carola-Bibiane, Aviles-Rivero, Angelica I
Partial differential equations (PDEs) are widely used to model complex physical systems, but solving them efficiently remains a significant challenge. Recently, Transformers have emerged as the preferred architecture for PDEs due to their ability to
Externí odkaz:
http://arxiv.org/abs/2410.02113
This paper investigates which alternative benefits from vote delegation in binary collective decisions within blockchains. We begin by examining two extreme cases of voting weight distributions: Equal-Weight (EW), where each voter has equal voting we
Externí odkaz:
http://arxiv.org/abs/2408.05410
The MEV-Boost block auction contributes approximately 90% of all Ethereum blocks. Between October 2023 and March 2024, only three builders produced 80% of them, highlighting the concentration of power within the block builder market. To foster compet
Externí odkaz:
http://arxiv.org/abs/2407.13931
Autor:
Ting, Yuan-Sen, Nguyen, Tuan Dung, Ghosal, Tirthankar, Pan, Rui, Arora, Hardik, Sun, Zechang, de Haan, Tijmen, Ramachandra, Nesar, Wells, Azton, Madireddy, Sandeep, Accomazzi, Alberto
We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy an
Externí odkaz:
http://arxiv.org/abs/2407.11194
Autor:
Lee, Hojoon, Cho, Hyeonseo, Kim, Hyunseung, Kim, Donghu, Min, Dugki, Choo, Jaegul, Lyle, Clare
This study investigates the loss of generalization ability in neural networks, revisiting warm-starting experiments from Ash & Adams. Our empirical analysis reveals that common methods designed to enhance plasticity by maintaining trainability provid
Externí odkaz:
http://arxiv.org/abs/2406.02596
Autor:
Steinmeister, Louis, Pauly, Markus
"If you ask ten experts, you will get ten different opinions." This common proverb illustrates the common association of expert forecasts with personal bias and lack of consistency. On the other hand, digitization promises consistency and explainabil
Externí odkaz:
http://arxiv.org/abs/2404.09334
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Zhang, Zhengyan, Song, Yixin, Yu, Guanghui, Han, Xu, Lin, Yankai, Xiao, Chaojun, Song, Chenyang, Liu, Zhiyuan, Mi, Zeyu, Sun, Maosong
Sparse computation offers a compelling solution for the inference of Large Language Models (LLMs) in low-resource scenarios by dynamically skipping the computation of inactive neurons. While traditional approaches focus on ReLU-based LLMs, leveraging
Externí odkaz:
http://arxiv.org/abs/2402.03804
Autor:
Zappalà, Chiara, Sousa, Sandro, Cunha, Tiago, Pluchino, Alessandro, Rapisarda, Andrea, Sinatra, Roberta
Success in sports is a complex phenomenon that has only garnered limited research attention. In particular, we lack a deep scientific understanding of success in sports like tennis and the factors that contribute to it. Here, we study the unfolding o
Externí odkaz:
http://arxiv.org/abs/2401.06479
Autor:
Valentina Gasser, Amrita Singh-Morgan, Magdalena Lederbauer, Mercede Azizbaig Mohajer, Elise Komarczuk
Publikováno v:
CHIMIA, Vol 78, Iss 6 (2024)
For this CHIMIA special issue on the United Nations Sustainable Development Goals (SDGs) and the coincidental 10th anniversary of the association of Women in Natural Sciences (WiNS) at ETH Zurich, there is no better opportunity to share what we have
Externí odkaz:
https://doaj.org/article/1cdc83ea349f4e0d8d0e05dc9304e534
