3 citations · 3 across the 6 of their papers we have counts for
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cs.LG2024
SELU: Self-Learning Embodied MLLMs in Unknown Environments
Boyu Li, Haobin Jiang, Ziluo Ding +4
Recently, multimodal large language models (MLLMs) have demonstrated strong visual understanding and decision-making capabilities, enabling the exploration of autonomously improvin…
cs.CV2024
Egocentric Vision Language Planning
Zhirui Fang, Ming Yang, Weishuai Zeng +5
We explore leveraging large multi-modal models (LMMs) and text2image models to build a more general embodied agent. LMMs excel in planning long-horizon tasks over symbolic abstract…
cs.AI2024★ 3 cited
Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu +25
Despite the success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encaps…