Zobrazeno 1 - 10
of 1 278 951
pro vyhledávání: '"A. Steer"'
Comparative Analysis of Adaptation Behaviors of Different Types of Drivers to Steer-by-Wire Systems.
Autor:
Chen, Chen1 (AUTHOR) chen_chen22@mails.jlu.edu.cn, Jin, Liqiang1 (AUTHOR), Zheng, Hongyu1 (AUTHOR) zhy_jlu@163.com, Zong, Changfu1 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2024, Vol. 24 Issue 17, p5562. 22p.
Autor:
Smith, Laura, Irpan, Alex, Arenas, Montserrat Gonzalez, Kirmani, Sean, Kalashnikov, Dmitry, Shah, Dhruv, Xiao, Ted
The complexity of the real world demands robotic systems that can intelligently adapt to unseen situations. We present STEER, a robot learning framework that bridges high-level, commonsense reasoning with precise, flexible low-level control. Our appr
Externí odkaz:
http://arxiv.org/abs/2411.03409
Traditional approaches to motion modeling for skid-steer robots struggle with capturing nonlinear tire-terrain dynamics, especially during high-speed maneuvers. In this paper, we tackle such nonlinearities by enhancing a dynamic unicycle model with G
Externí odkaz:
http://arxiv.org/abs/2411.03289
Conversational AI models are becoming increasingly popular and are about to replace traditional search engines for information retrieval and product discovery. This raises concerns about monetization strategies and the potential for subtle consumer m
Externí odkaz:
http://arxiv.org/abs/2409.12143
This paper considers an ergodic version of the bounded velocity follower problem, assuming that the decision maker lacks knowledge of the underlying system parameters and must learn them while simultaneously controlling. We propose algorithms based o
Externí odkaz:
http://arxiv.org/abs/2410.03221
Large language models (LLMs) can generate fluent summaries across domains using prompting techniques, reducing the need to train models for summarization applications. However, crafting effective prompts that guide LLMs to generate summaries with the
Externí odkaz:
http://arxiv.org/abs/2410.02741
Designing incentives for an adapting population is a ubiquitous problem in a wide array of economic applications and beyond. In this work, we study how to design additional rewards to steer multi-agent systems towards desired policies \emph{without}
Externí odkaz:
http://arxiv.org/abs/2407.10207
Autor:
Ward, Logan, Pauloski, J. Gregory, Hayot-Sasson, Valerie, Babuji, Yadu, Brace, Alexander, Chard, Ryan, Chard, Kyle, Thakur, Rajeev, Foster, Ian
Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of their capabilities. We created Colmena to leverage the massive parallelis
Externí odkaz:
http://arxiv.org/abs/2408.14434
With the goal of building a system capable of controllable symbolic music loop generation and editing, this paper explores a generalisation of Masked Language Modelling we call Superposed Language Modelling. Rather than input tokens being known or un
Externí odkaz:
http://arxiv.org/abs/2408.02434
Autor:
Gavrikov, Paul, Lukasik, Jovita, Jung, Steffen, Geirhos, Robert, Lamm, Bianca, Mirza, Muhammad Jehanzeb, Keuper, Margret, Keuper, Janis
Vision language models (VLMs) have drastically changed the computer vision model landscape in only a few years, opening an exciting array of new applications from zero-shot image classification, over to image captioning, and visual question answering
Externí odkaz:
http://arxiv.org/abs/2403.09193