June 7, 2024, 4:43 a.m. | Jingyao Li, Pengguang Chen, Sitong Wu, Chuanyang Zheng, Hong Xu, Jiaya Jia

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.03757v1 Announce Type: cross
Abstract: The emergence of Large Language Models (LLMs) has improved the prospects for robotic tasks. However, existing benchmarks are still limited to single tasks with limited generalization capabilities. In this work, we introduce a comprehensive benchmark and an autonomous learning framework, RoboCoder aimed at enhancing the generalization capabilities of robots in complex environments. Unlike traditional methods that focus on single-task learning, our research emphasizes the development of a general-purpose robotic coding algorithm that enables robots to …

abstract arxiv autonomous basic benchmark benchmarks capabilities cs.lg cs.ro emergence framework general however language language models large language large language models llms prospects robotic robotic learning skills tasks type work

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