Zobrazeno 1 - 10
of 9 473
pro vyhledávání: '"P. Schlesinger"'
Using Large Language Models (LLMs) to produce robot programs from natural language has allowed for robot systems that can complete a higher diversity of tasks. However, LLM-generated programs may be faulty, either due to ambiguity in instructions, mi
Externí odkaz:
http://arxiv.org/abs/2410.18893
Traditional machine learning methods applied to the material sciences have often predicted invariant, scalar properties of material systems to great effect. Newer, coordinate equivariant models promise to provide a coordinate system dependent output
Externí odkaz:
http://arxiv.org/abs/2406.03563
Autor:
Fang, Jennifer C., Kawas, M. J., Zou, J., Gopalan, V., Schlesinger, T. E., Stancil, Daniel D.
Publikováno v:
IEEE Photonics Technology Letters ( Volume: 11, Issue: 1, January 1999)
A new horn-shaped electrooptic scanner is described with significantly improved scanning sensitivity over rectangular-shaped devices. In the new device, the shape of the scanner is chosen to follow the trajectory of the beam. An example design is des
Externí odkaz:
http://arxiv.org/abs/2405.05540
Autor:
Moeller, Mark, Jacobs, Jules, Belanger, Olivier Savary, Darais, David, Schlesinger, Cole, Smolka, Steffen, Foster, Nate, Silva, Alexandra
We develop new data structures and algorithms for checking verification queries in NetKAT, a domain-specific language for specifying the behavior of network data planes. Our results extend the techniques obtained in prior work on symbolic automata an
Externí odkaz:
http://arxiv.org/abs/2404.04760
We study the principal-agent setting, where a principal delegates the execution of a costly project to an agent. In the classical model, the agent chooses an action among a set of available actions. Every action is associated with some cost, and lead
Externí odkaz:
http://arxiv.org/abs/2403.09545
Autor:
Hu, Zichao, Lucchetti, Francesca, Schlesinger, Claire, Saxena, Yash, Freeman, Anders, Modak, Sadanand, Guha, Arjun, Biswas, Joydeep
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 3, pp. 2853-2860, March 2024
Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We investigate the use of LLMs to generate programs for service mobile robots
Externí odkaz:
http://arxiv.org/abs/2311.11183
Autor:
Katrin Müller, Iris Poppele, Marcel Ottiger, Alois Wastlhuber, Rainer-Christian Weber, Michael Stegbauer, Torsten Schlesinger
Publikováno v:
Journal of Occupational Medicine and Toxicology, Vol 19, Iss 1, Pp 1-14 (2024)
Abstract Background Rehabilitation plays a crucial role in restoring work ability and facilitating the reintegration of post-COVID patients into the workforce. The impact of rehabilitation on work ability and return to work (RTW) of post-COVID patien
Externí odkaz:
https://doaj.org/article/03dfde9001c54ff1861c965c63b9fd10
Autor:
Cassano, Federico, Gouwar, John, Lucchetti, Francesca, Schlesinger, Claire, Freeman, Anders, Anderson, Carolyn Jane, Feldman, Molly Q, Greenberg, Michael, Jangda, Abhinav, Guha, Arjun
Over the past few years, Large Language Models of Code (Code LLMs) have started to have a significant impact on programming practice. Code LLMs are also emerging as building blocks for research in programming languages and software engineering. Howev
Externí odkaz:
http://arxiv.org/abs/2308.09895
We view variational autoencoders (VAE) as decoder-encoder pairs, which map distributions in the data space to distributions in the latent space and vice versa. The standard learning approach for VAEs is the maximisation of the evidence lower bound (E
Externí odkaz:
http://arxiv.org/abs/2307.09883
Autor:
Li, Raymond, Allal, Loubna Ben, Zi, Yangtian, Muennighoff, Niklas, Kocetkov, Denis, Mou, Chenghao, Marone, Marc, Akiki, Christopher, Li, Jia, Chim, Jenny, Liu, Qian, Zheltonozhskii, Evgenii, Zhuo, Terry Yue, Wang, Thomas, Dehaene, Olivier, Davaadorj, Mishig, Lamy-Poirier, Joel, Monteiro, João, Shliazhko, Oleh, Gontier, Nicolas, Meade, Nicholas, Zebaze, Armel, Yee, Ming-Ho, Umapathi, Logesh Kumar, Zhu, Jian, Lipkin, Benjamin, Oblokulov, Muhtasham, Wang, Zhiruo, Murthy, Rudra, Stillerman, Jason, Patel, Siva Sankalp, Abulkhanov, Dmitry, Zocca, Marco, Dey, Manan, Zhang, Zhihan, Fahmy, Nour, Bhattacharyya, Urvashi, Yu, Wenhao, Singh, Swayam, Luccioni, Sasha, Villegas, Paulo, Kunakov, Maxim, Zhdanov, Fedor, Romero, Manuel, Lee, Tony, Timor, Nadav, Ding, Jennifer, Schlesinger, Claire, Schoelkopf, Hailey, Ebert, Jan, Dao, Tri, Mishra, Mayank, Gu, Alex, Robinson, Jennifer, Anderson, Carolyn Jane, Dolan-Gavitt, Brendan, Contractor, Danish, Reddy, Siva, Fried, Daniel, Bahdanau, Dzmitry, Jernite, Yacine, Ferrandis, Carlos Muñoz, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, de Vries, Harm
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilitie
Externí odkaz:
http://arxiv.org/abs/2305.06161