Language Based Representation

Language-based representation research focuses on encoding and utilizing natural language to improve various AI tasks, primarily aiming to bridge the gap between human-understandable instructions and machine execution. Current efforts concentrate on integrating language models with other modalities (e.g., vision, robotics) using techniques like contrastive learning and embedding language features into 3D representations, often leveraging transformer architectures. This work is significant for advancing embodied AI, improving the safety and explainability of autonomous systems, and enabling more robust and context-aware natural language processing across diverse languages and applications.