2 citations · 2 across the 5 of their papers we have counts for
5 papers
First Things First: Teaching LLM-Based Agents to Prioritize Must-Haves before Nice-to-Haves
Tianjie Ju, Xinyue Xu, Wanxuan Sun +4
Recent progress in multimodal large language models (MLLMs) has fueled significant enthusiasm in their potential to act as autonomous agents for real-world tasks. However, scenario…
DexCanvas: Bridging Human Demonstrations and Robot Learning for Dexterous Manipulation
Xinyue Xu, Jieqiang Sun, Jing +9
We present DexCanvas, a large-scale hybrid real-synthetic human manipulation dataset containing 7,000 hours of dexterous hand-object interactions seeded from 70 hours of real human…
GuideBench: Benchmarking Domain-Oriented Guideline Following for LLM Agents
Lingxiao Diao, Xinyue Xu, Wanxuan Sun +2
Large language models (LLMs) have been widely deployed as autonomous agents capable of following user instructions and making decisions in real-world applications. Previous studies…
DISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level Control
Xinyu Xu, Shengcheng Luo, Yanchao Yang +2
Building a general-purpose intelligent home-assistant agent skilled in diverse tasks by human commands is a long-term blueprint of embodied AI research, which poses requirements on…
HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid
Xinyu Xu, Yizheng Zhang, Yong-Lu Li +2
Physical Human-Scene Interaction (HSI) plays a crucial role in numerous applications. However, existing HSI techniques are limited to specific object dynamics and privileged inform…