29 citations · 108 across the 19 of their papers we have counts for
4 papers · 1 filter
SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation
Chunjiang Liu, Xiaoyuan Wang, Haoyu Chen +3
LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output. Dynamic 4D scenes from text alone, i…
ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes
Ran Gong, Jiangyong Huang, Yizhou Zhao +9
Understanding the continuous states of objects is essential for task learning and planning in the real world. However, most existing task learning benchmarks assume discrete (e.g.,…
LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
Yizhou Zhao, Kaixiang Lin, Zhiwei Jia +4
Learning-based methods for training embodied agents typically require a large number of high-quality scenes that contain realistic layouts and support meaningful interactions. Howe…
Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative Tasks
Xiaofeng Gao, Ran Gong, Yizhou Zhao +3
Human collaborators can effectively communicate with their partners to finish a common task by inferring each other's mental states (e.g., goals, beliefs, and desires). Such mind-a…