May 14, 2024, 4:43 a.m. | Akhil Arora, Lars Klein, Nearchos Potamitis, Roland Aydin, Caglar Gulcehre, Robert West

cs.LG updates on

arXiv:2405.06691v1 Announce Type: cross
Abstract: Large language models (LLMs) have significantly evolved, moving from simple output generation to complex reasoning and from stand-alone usage to being embedded into broader frameworks. In this paper, we introduce \emph{Fleet of Agents (FoA)}, a novel framework utilizing LLMs as agents to navigate through dynamic tree searches, employing a genetic-type particle filtering approach. FoA spawns a multitude of agents, each exploring autonomously, followed by a selection phase where resampling based on a heuristic value function …

abstract agents arxiv cs.lg embedded filtering framework frameworks language language models large language large language models llms moving novel paper particle reasoning simple type usage

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