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pro vyhledávání: '"Sterbentz, Marko"'
Autor:
Sterbentz, Marko, Barrie, Cameron, Shahi, Shubham, Dutta, Abhratanu, Hooshmand, Donna, Pack, Harper, Hammond, Kristian J.
Large language models (LLMs) are capable of producing documents, and retrieval augmented generation (RAG) has shown itself to be a powerful method for improving accuracy without sacrificing fluency. However, not all information can be retrieved from
Externí odkaz:
http://arxiv.org/abs/2406.12069
Autor:
Sterbentz, Marko, Barrie, Cameron, Hooshmand, Donna, Shahi, Shubham, Dutta, Abhratanu, Pack, Harper, Zhao, Andong Li, Paley, Andrew, Einarsson, Alexander, Hammond, Kristian
The principal goal of data science is to derive meaningful information from data. To do this, data scientists develop a space of analytic possibilities and from it reach their information goals by using their knowledge of the domain, the available da
Externí odkaz:
http://arxiv.org/abs/2311.12848
Autor:
Demeter, David, Agarwal, Oshin, Igeri, Simon Ben, Sterbentz, Marko, Molino, Neil, Conroy, John M., Nenkova, Ani
Academic literature does not give much guidance on how to build the best possible customer-facing summarization system from existing research components. Here we present analyses to inform the selection of a system backbone from popular models; we fi
Externí odkaz:
http://arxiv.org/abs/2306.10555
Autor:
Zhao, Andong Luis Li, Paley, Andrew, Adler, Rachel, Pack, Harper, Servantez, Sergio, Einarsson, Alexander, Barrie, Cameron, Sterbentz, Marko, Hammond, Kristian
A politically informed citizenry is imperative for a welldeveloped democracy. While the US government has pursued policies for open data, these efforts have been insufficient in achieving an open government because only people with technical and doma
Externí odkaz:
http://arxiv.org/abs/2112.03119