Zobrazeno 1 - 10
of 4 986
pro vyhledávání: '"ERICSON, A. P."'
Acquisition and maintenance are central problems in deploying high-definition (HD) maps for autonomous driving, with two lines of research prevalent in current literature: Online HD map generation and HD map change detection. However, the generated m
Externí odkaz:
http://arxiv.org/abs/2409.10178
Autor:
Vieira, J., Cros, B., Muggli, P., Andriyash, I. A., Apsimon, O., Backhouse, M., Benedetti, C., Bulanov, S. S., Caldwell, A., Chen, Min, Cilento, V., Corde, S., D'Arcy, R., Diederichs, S., Ericson, E., Esarey, E., Farmer, J., Fedeli, L., Formenti, A., Foster, B., Garten, M., Geddes, C. G. R., Grismayer, T., Hogan, M. J., Hooker, S., Huebl, A., Jalas, S., Kirchen, M., Lehe, R., Leemans, W., Li, Boyuan, Lindström, C. A., Losito, R., Mitchell, C. E., Mori, W. B., Piot, P., Terzani, D., Thévenet, M., Turner, M., Vay, J. -L., Völker, D., Zhang, Jie, Zhang, W.
The workshop focused on the application of ANAs to particle physics keeping in mind the ultimate goal of a collider at the energy frontier (10\,TeV, e$^+$/e$^-$, e$^-$/e$^-$, or $\gamma\gamma$). The development of ANAs is conducted at universities an
Externí odkaz:
http://arxiv.org/abs/2408.03968
Autor:
Lindström, Adam Dahlgren, Methnani, Leila, Krause, Lea, Ericson, Petter, de Troya, Íñigo Martínez de Rituerto, Mollo, Dimitri Coelho, Dobbe, Roel
This paper critically evaluates the attempts to align Artificial Intelligence (AI) systems, especially Large Language Models (LLMs), with human values and intentions through Reinforcement Learning from Feedback (RLxF) methods, involving either human
Externí odkaz:
http://arxiv.org/abs/2406.18346
Autor:
Ericson, Ludvig, Jensfelt, Patric
Publikováno v:
IEEE Robotics and Automation Letters (2024) pp. 2377-3766
In this paper, we tackle the challenge of predicting the unseen walls of a partially observed environment as a set of 2D line segments, conditioned on occupancy grids integrated along the trajectory of a 360{\deg} LIDAR sensor. A dataset of such occu
Externí odkaz:
http://arxiv.org/abs/2406.09160
Autor:
Padiyath, Aadarsh, Hou, Xinying, Pang, Amy, Vargas, Diego Viramontes, Gu, Xingjian, Nelson-Fromm, Tamara, Wu, Zihan, Guzdial, Mark, Ericson, Barbara
The capability of large language models (LLMs) to generate, debug, and explain code has sparked the interest of researchers and educators in undergraduate programming, with many anticipating their transformative potential in programming education. Ho
Externí odkaz:
http://arxiv.org/abs/2406.06451
The ionosphere affects radio signals by altering their speed, direction, and trajectory, causing a temporary delay known as ionospheric delay, which is directly related to the total electron content (TEC). Although research in other equatorial locati
Externí odkaz:
http://arxiv.org/abs/2403.19053
CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming
Learning to program can be challenging, and providing high-quality and timely support at scale is hard. Generative AI and its products, like ChatGPT, can create a solution for most intro-level programming problems. However, students might use these t
Externí odkaz:
http://arxiv.org/abs/2401.12125
In the financial services industry, forecasting the risk factor distribution conditional on the history and the current market environment is the key to market risk modeling in general and value at risk (VaR) model in particular. As one of the most w
Externí odkaz:
http://arxiv.org/abs/2401.10370
Novice programmers need to write basic code as part of the learning process, but they often face difficulties. To assist struggling students, we recently implemented personalized Parsons problems, which are code puzzles where students arrange blocks
Externí odkaz:
http://arxiv.org/abs/2401.03144
Computing artifacts tend to exclude marginalized students, so we must create new methods to critique and change them. We studied the potential for "satirical programming" to critique artifacts as part of culturally responsive computing (CRC) pedagogy
Externí odkaz:
http://arxiv.org/abs/2312.03090