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pro vyhledávání: '"Lála, Jakub"'
Autor:
Lála, Jakub, O'Donoghue, Odhran, Shtedritski, Aleksandar, Cox, Sam, Rodriques, Samuel G., White, Andrew D.
Large Language Models (LLMs) generalize well across language tasks, but suffer from hallucinations and uninterpretability, making it difficult to assess their accuracy without ground-truth. Retrieval-Augmented Generation (RAG) models have been propos
Externí odkaz:
http://arxiv.org/abs/2312.07559
Autor:
Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D., Bran, Andres M, Bringuier, Stefan, Brinson, L. Catherine, Choudhary, Kamal, Circi, Defne, Cox, Sam, de Jong, Wibe A., Evans, Matthew L., Gastellu, Nicolas, Genzling, Jerome, Gil, María Victoria, Gupta, Ankur K., Hong, Zhi, Imran, Alishba, Kruschwitz, Sabine, Labarre, Anne, Lála, Jakub, Liu, Tao, Ma, Steven, Majumdar, Sauradeep, Merz, Garrett W., Moitessier, Nicolas, Moubarak, Elias, Mouriño, Beatriz, Pelkie, Brenden, Pieler, Michael, Ramos, Mayk Caldas, Ranković, Bojana, Rodriques, Samuel G., Sanders, Jacob N., Schwaller, Philippe, Schwarting, Marcus, Shi, Jiale, Smit, Berend, Smith, Ben E., Van Herck, Joren, Völker, Christoph, Ward, Logan, Warren, Sean, Weiser, Benjamin, Zhang, Sylvester, Zhang, Xiaoqi, Zia, Ghezal Ahmad, Scourtas, Aristana, Schmidt, KJ, Foster, Ian, White, Andrew D., Blaiszik, Ben
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article c
Externí odkaz:
http://arxiv.org/abs/2306.06283