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Found 8 papers, 0 papers with code
STEVE Series: Step-by-Step Construction of Agent Systems in Minecraft
We begin our exploration with a vanilla large language model, augmenting it with a vision encoder and an action codebase trained on our collected high-quality dataset STEVE-21K.
CityCraft: A Real Crafter for 3D City Generation
The rendered scenes lack variety, resembling the training images, resulting in monotonous styles.
Do We Really Need a Complex Agent System? Distill Embodied Agent into a Single Model
After distillation, embodied agents can complete complex, open-ended tasks without additional expert guidance, utilizing the performance and knowledge of a versatile MLM.
Hierarchical Auto-Organizing System for Open-Ended Multi-Agent Navigation
To assess organizational behavior, we design a series of navigation tasks in the Minecraft environment, which includes searching and exploring.
See and Think: Embodied Agent in Virtual Environment
This paper proposes STEVE, a comprehensive and visionary embodied agent in the Minecraft virtual environment.
Devil in the Number: Towards Robust Multi-modality Data Filter
In order to appropriately filter multi-modality data sets on a web-scale, it becomes crucial to employ suitable filtering methods to boost performance and reduce training costs.
A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision.
