Feb. 20, 2024, 5:51 a.m. | Xinbei Ma, Zhuosheng Zhang, Hai Zhao

cs.CL updates on arXiv.org arxiv.org

arXiv:2402.11941v1 Announce Type: new
Abstract: Large language models (LLMs) have shown remarkable potential as human-like autonomous language agents to interact with real-world environments, especially for graphical user interface (GUI) automation. However, those GUI agents require comprehensive cognition ability including exhaustive perception and reliable action response. We propose \underline{Co}mprehensive \underline{Co}gnitive LLM \underline{Agent}, CoCo-Agent, with two novel approaches, comprehensive environment perception (CEP) and conditional action prediction (CAP), to systematically improve the GUI automation performance. First, CEP facilitates the GUI perception through different …

abstract agent agents arxiv automation autonomous coco cognition cognitive cs.cl environments gui human human-like language language models large language large language models llm llms perception smartphone type world

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