Zobrazeno 1 - 10
of 970
pro vyhledávání: '"Patil, P. G."'
Autor:
Patil, Shishir G., Zhang, Tianjun, Fang, Vivian, C., Noppapon, Huang, Roy, Hao, Aaron, Casado, Martin, Gonzalez, Joseph E., Popa, Raluca Ada, Stoica, Ion
Large Language Models (LLMs) are evolving beyond their classical role of providing information within dialogue systems to actively engaging with tools and performing actions on real-world applications and services. Today, humans verify the correctnes
Externí odkaz:
http://arxiv.org/abs/2404.06921
Autor:
Zhang, Tianjun, Patil, Shishir G., Jain, Naman, Shen, Sheng, Zaharia, Matei, Stoica, Ion, Gonzalez, Joseph E.
Pretraining Large Language Models (LLMs) on large corpora of textual data is now a standard paradigm. When using these LLMs for many downstream applications, it is common to additionally bake in new knowledge (e.g., time-critical news, or private dom
Externí odkaz:
http://arxiv.org/abs/2403.10131
Autor:
Packer, Charles, Wooders, Sarah, Lin, Kevin, Fang, Vivian, Patil, Shishir G., Stoica, Ion, Gonzalez, Joseph E.
Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis. To enable using context beyond limited context windows, we propos
Externí odkaz:
http://arxiv.org/abs/2310.08560
Large Language Models (LLMs) have seen an impressive wave of advances recently, with models now excelling in a variety of tasks, such as mathematical reasoning and program synthesis. However, their potential to effectively use tools via API calls rem
Externí odkaz:
http://arxiv.org/abs/2305.15334
Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applications. We demonstrate that it is possible to significantly improve in
Externí odkaz:
http://arxiv.org/abs/2210.07259
Fine-tuning models on edge devices like mobile phones would enable privacy-preserving personalization over sensitive data. However, edge training has historically been limited to relatively small models with simple architectures because training is b
Externí odkaz:
http://arxiv.org/abs/2207.07697
Publikováno v:
Nature Environment and Pollution Technology, Vol 22, Iss 4, Pp 2093-2101 (2023)
In this study, three promising yeast isolates were isolated from the sap of the Indian date palm tree (Phoenix sylvestris) and characterized by biochemical tests and 18S rRNA gene sequencing. They were confirmed as Saccharomyces cerevisiae and were d
Externí odkaz:
https://doaj.org/article/c1bc1f9a42254ccdbf3dd6507541d787
Publikováno v:
Nature Environment and Pollution Technology, Vol 22, Iss 2, Pp 1041-1045 (2023)
In recent years, there has been a significant increase in the needs of the overgrowing population. Naturally, industrial belts increased worldwide to satisfy the variety and quantity of needs. While producing the products, a huge quantity of waste is
Externí odkaz:
https://doaj.org/article/82da7c44325e484ab8ac19c6367204f3
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.