Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Marchi, Matteo"'
We tackle the question of whether Large Language Models (LLMs), viewed as dynamical systems with state evolving in the embedding space of symbolic tokens, are observable. That is, whether there exist multiple 'mental' state trajectories that yield th
Externí odkaz:
http://arxiv.org/abs/2405.14061
Improvement and adoption of generative machine learning models is rapidly accelerating, as exemplified by the popularity of LLMs (Large Language Models) for text, and diffusion models for image generation. As generative models become widespread, data
Externí odkaz:
http://arxiv.org/abs/2404.02325
Optimization algorithms have a rich and fundamental relationship with ordinary differential equations given by its continuous-time limit. When the cost function varies with time -- typically in response to a dynamically changing environment -- online
Externí odkaz:
http://arxiv.org/abs/2403.19088
Publikováno v:
In Safety Science April 2025 184
Dirty derivatives are routinely used in industrial settings, particularly in the implementation of the derivative term in PID control, and are especially appealing due to their noise-attenuation and model-free characteristics. In this paper, we provi
Externí odkaz:
http://arxiv.org/abs/2202.01941
In this paper we propose a methodology for stabilizing single-input single-output feedback linearizable systems when no system model is known and no prior data is available to identify a model. Conceptually, we have been greatly inspired by the work
Externí odkaz:
http://arxiv.org/abs/2003.14240
Publikováno v:
In Applied Ergonomics October 2022 104
Publikováno v:
In Procedia CIRP 2021 96:278-283
Autor:
Aruväli, Tanel1 (AUTHOR) tanel.aruvaeli@unibz.it, De Marchi, Matteo1 (AUTHOR), Rauch, Erwin1 (AUTHOR)
Publikováno v:
Scientific Reports. 2/20/2023, Vol. 13 Issue 1, p1-16. 16p.
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