Zobrazeno 1 - 10
of 7 881
pro vyhledávání: '"A. Jaekel"'
Autor:
Thellmann, Klaudia, Stadler, Bernhard, Fromm, Michael, Buschhoff, Jasper Schulze, Jude, Alex, Barth, Fabio, Leveling, Johannes, Flores-Herr, Nicolas, Köhler, Joachim, Jäkel, René, Ali, Mehdi
The rise of Large Language Models (LLMs) has revolutionized natural language processing across numerous languages and tasks. However, evaluating LLM performance in a consistent and meaningful way across multiple European languages remains challenging
Externí odkaz:
http://arxiv.org/abs/2410.08928
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
CAD models are widely used in industry and are essential for robotic automation processes. However, these models are rarely considered in novel AI-based approaches, such as the automatic synthesis of robot programs, as there are no readily available
Externí odkaz:
http://arxiv.org/abs/2409.08704
This paper presents SPI-DP, a novel first-order optimizer capable of optimizing robot programs with respect to both high-level task objectives and motion-level constraints. To that end, we introduce DGPMP2-ND, a differentiable collision-free motion p
Externí odkaz:
http://arxiv.org/abs/2409.08678
In this paper, the proximal decoding algorithm is considered within the context of additive white Gaussian noise (AWGN) channels. An analysis of the convergence behavior of the algorithm shows that proximal decoding inherently enters an oscillating b
Externí odkaz:
http://arxiv.org/abs/2409.07278
Autor:
Kienle, Claudius, Alt, Benjamin, Celik, Onur, Becker, Philipp, Katic, Darko, Jäkel, Rainer, Neumann, Gerhard
High-level robot skills represent an increasingly popular paradigm in robot programming. However, configuring the skills' parameters for a specific task remains a manual and time-consuming endeavor. Existing approaches for learning or optimizing thes
Externí odkaz:
http://arxiv.org/abs/2407.15660
Autor:
Mandelbaum, Jonathan, Miao, Sisi, Schwendemann, Nils Albert, Jäkel, Holger, Schmalen, Laurent
With the increasing demands on future wireless systems, new design objectives become eminent. Low-density parity-check codes together with belief propagation (BP) decoding have outstanding performance for large block lengths. Yet, for future wireless
Externí odkaz:
http://arxiv.org/abs/2406.02012
Autor:
Alt, Benjamin, Zahn, Johannes, Kienle, Claudius, Dvorak, Julia, May, Marvin, Katic, Darko, Jäkel, Rainer, Kopp, Tobias, Beetz, Michael, Lanza, Gisela
While recent advances in deep learning have demonstrated its transformative potential, its adoption for real-world manufacturing applications remains limited. We present an Explanation User Interface (XUI) for a state-of-the-art deep learning-based r
Externí odkaz:
http://arxiv.org/abs/2404.19349
Over the past decade, deep learning helped solve manipulation problems across all domains of robotics. At the same time, industrial robots continue to be programmed overwhelmingly using traditional program representations and interfaces. This paper u
Externí odkaz:
http://arxiv.org/abs/2404.13652
Autor:
Alt, Benjamin, Stöckl, Florian, Müller, Silvan, Braun, Christopher, Raible, Julian, Alhasan, Saad, Rettig, Oliver, Ringle, Lukas, Katic, Darko, Jäkel, Rainer, Beetz, Michael, Strand, Marcus, Huber, Marco F.
Surface treatment tasks such as grinding, sanding or polishing are a vital step of the value chain in many industries, but are notoriously challenging to automate. We present RoboGrind, an integrated system for the intuitive, interactive automation o
Externí odkaz:
http://arxiv.org/abs/2402.16542