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pro vyhledávání: '"A Sohrabi"'
There is an increasing body of work using Large Language Models (LLMs) as agents for orchestrating workflows and making decisions in domains that require planning and multi-step reasoning. As a result, it is imperative to evaluate LLMs on core skills
Externí odkaz:
http://arxiv.org/abs/2410.05669
Publikováno v:
International Journal of Hydrogen Energy, 89 (2024):1060-1074
This paper examines the electrification of transportation as a response to environmental challenges caused by fossil fuels, exploring the potential of battery electric vehicles and hydrogen fuel cell vehicles as alternative solutions. However, a sign
Externí odkaz:
http://arxiv.org/abs/2410.03763
The process of translating a quantum algorithm into a form suitable for implementation on a quantum computing platform is crucial but yet challenging. This entails specifying quantum operations with precision, a typically intricate task. In this pape
Externí odkaz:
http://arxiv.org/abs/2408.13211
Planning remains one of the last standing bastions for large language models (LLMs), which now turn their attention to search. Most of the literature uses the language models as world models to define the search space, forgoing soundness for the sake
Externí odkaz:
http://arxiv.org/abs/2408.11326
Autor:
Sohrabi, Motahareh, Ramirez, Juan, Zhang, Tianyue H., Lacoste-Julien, Simon, Gallego-Posada, Jose
Constrained optimization offers a powerful framework to prescribe desired behaviors in neural network models. Typically, constrained problems are solved via their min-max Lagrangian formulations, which exhibit unstable oscillatory dynamics when optim
Externí odkaz:
http://arxiv.org/abs/2406.04558
Autor:
Myasnikov, Alexei G., Sohrabi, Mahmood
In this paper we describe all groups that are first-order (elementarily) equivalent to the classical matrix groups such as $GL_n(F), SL_n(F)$ and $T_n(F)$ over a field $F$ provided $n \geq 3$.
Comment: 36 pages
Comment: 36 pages
Externí odkaz:
http://arxiv.org/abs/2405.14476
Among the most important properties of algorithms investigated in computer science are soundness, completeness, and complexity. These properties, however, are rarely analyzed for the vast collection of recently proposed methods for planning with larg
Externí odkaz:
http://arxiv.org/abs/2404.11833
Developing domain models is one of the few remaining places that require manual human labor in AI planning. Thus, in order to make planning more accessible, it is desirable to automate the process of domain model generation. To this end, we investiga
Externí odkaz:
http://arxiv.org/abs/2405.06650
The ability to generate multiple plans is central to using planning in real-life applications. Top-quality planners generate sets of such top-cost plans, allowing flexibility in determining equivalent ones. In terms of the order between actions in a
Externí odkaz:
http://arxiv.org/abs/2404.01503
The growing utilization of planning tools in practical scenarios has sparked an interest in generating multiple high-quality plans. Consequently, a range of computational problems under the general umbrella of top-quality planning were introduced ove
Externí odkaz:
http://arxiv.org/abs/2403.03176