Breaking Ground in 3D-Language Models
Combating hallucination through robust 3D environment grounding
3D-GRAND introduces the first million-scale dataset for training language models that accurately understand and interact with 3D environments.
- Creates densely grounded connections between language and 3D scenes
- Significantly reduces hallucination in embodied AI systems
- Enables robots and agents to better comprehend physical spaces
- Provides foundation for next-generation perception systems
This research represents a critical advancement for engineering embodied agents that can safely navigate and interact with real-world environments through improved spatial understanding and reduced false perceptions.