Zobrazeno 1 - 10
of 28 758
pro vyhledávání: '"Rehm, A"'
Recent advancements in large language models (LLMs) have led to their increased application across various tasks, with reinforcement learning from human feedback (RLHF) being a crucial part of their training to align responses with user intentions. I
Externí odkaz:
http://arxiv.org/abs/2410.20869
Autor:
Rehm, Oliver, Baumgarten, Lutz, Guido, Roberto, Düring, Pia Maria, Gloskovskii, Andrei, Schlueter, Christoph, Mikolajick, Thomas, Schroeder, Uwe, Müller, Martina
Aluminum scandium nitride (Al$_{1-x}$Sc$_x$N) is a promising material for ferroelectric devices due to its large remanent polarization, scalability, and compatibility with semiconductor technology. By doping AlN with Sc, the bonds in the polar AlN st
Externí odkaz:
http://arxiv.org/abs/2410.21132
Autor:
Brandizzi, Nicolo', Abdelwahab, Hammam, Bhowmick, Anirban, Helmer, Lennard, Stein, Benny Jörg, Denisov, Pavel, Saleem, Qasid, Fromm, Michael, Ali, Mehdi, Rutmann, Richard, Naderi, Farzad, Agy, Mohamad Saif, Schwirjow, Alexander, Küch, Fabian, Hahn, Luzian, Ostendorff, Malte, Suarez, Pedro Ortiz, Rehm, Georg, Wegener, Dennis, Flores-Herr, Nicolas, Köhler, Joachim, Leveling, Johannes
This paper presents a comprehensive overview of the data preparation pipeline developed for the OpenGPT-X project, a large-scale initiative aimed at creating open and high-performance multilingual large language models (LLMs). The project goal is to
Externí odkaz:
http://arxiv.org/abs/2410.08800
Autor:
Ali, Mehdi, Fromm, Michael, Thellmann, Klaudia, Ebert, Jan, Weber, Alexander Arno, Rutmann, Richard, Jain, Charvi, Lübbering, Max, Steinigen, Daniel, Leveling, Johannes, Klug, Katrin, Buschhoff, Jasper Schulze, Jurkschat, Lena, Abdelwahab, Hammam, Stein, Benny Jörg, Sylla, Karl-Heinz, Denisov, Pavel, Brandizzi, Nicolo', Saleem, Qasid, Bhowmick, Anirban, Helmer, Lennard, John, Chelsea, Suarez, Pedro Ortiz, Ostendorff, Malte, Jude, Alex, Manjunath, Lalith, Weinbach, Samuel, Penke, Carolin, Filatov, Oleg, Asaadi, Shima, Barth, Fabio, Sifa, Rafet, Küch, Fabian, Herten, Andreas, Jäkel, René, Rehm, Georg, Kesselheim, Stefan, Köhler, Joachim, Flores-Herr, Nicolas
We present two multilingual LLMs designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European Union. Trained on a dataset comprising around 60% non-English data and utilizing a custom multilingual tokenize
Externí odkaz:
http://arxiv.org/abs/2410.03730
Autor:
Piñeiro-Martín, Andrés, García-Mateo, Carmen, Docío-Fernández, Laura, López-Pérez, María del Carmen, Rehm, Georg
Publikováno v:
Proceedings of Interspeech 2024
This paper addresses the challenge of integrating low-resource languages into multilingual automatic speech recognition (ASR) systems. We introduce a novel application of weighted cross-entropy, typically used for unbalanced datasets, to facilitate t
Externí odkaz:
http://arxiv.org/abs/2409.16954
Initially introduced as a machine translation model, the Transformer architecture has now become the foundation for modern deep learning architecture, with applications in a wide range of fields, from computer vision to natural language processing. N
Externí odkaz:
http://arxiv.org/abs/2406.06366
Autor:
Sulc, Antonin, Bien, Alex, Eichler, Annika, Ratner, Daniel, Rehm, Florian, Mayet, Frank, Hartmann, Gregor, Hoschouer, Hayden, Tuennermann, Henrik, Kaiser, Jan, John, Jason St., Maldonado, Jennefer, Hazelwood, Kyle, Kammering, Raimund, Hellert, Thorsten, Wilksen, Tim, Kain, Verena, Hu, Wan-Lin
Electronic logbooks contain valuable information about activities and events concerning their associated particle accelerator facilities. However, the highly technical nature of logbook entries can hinder their usability and automation. As natural la
Externí odkaz:
http://arxiv.org/abs/2406.12881
Numerical computations of stellar oscillations for models representative of B-type stars predict fewer modes to be excited than observations reveal from modern space-based photometric data. One shortcoming of state-of-the-art evolution models of B-ty
Externí odkaz:
http://arxiv.org/abs/2405.08864
Autor:
Dubovskiy, Andre, Criss, Troy, Valli, Ahmed Sidi El, Rehm, Laura, Kent, Andrew D., Haas, Andrew
Publikováno v:
IEEE Magnetics Letters 2024
Large quantities of random numbers are crucial in a wide range of applications. We have recently demonstrated that perpendicular nanopillar magnetic tunnel junctions (pMTJs) can produce true random bits when actuated with short pulses. However, our i
Externí odkaz:
http://arxiv.org/abs/2404.14307
Language models are trained mostly on Web data, which often contains social stereotypes and biases that the models can inherit. This has potentially negative consequences, as models can amplify these biases in downstream tasks or applications. Howeve
Externí odkaz:
http://arxiv.org/abs/2404.11726