Grounded language learning

Grounded language learning is a subfield of natural language processing that focuses on acquiring the meaning of language in concrete contexts. This task achieves a deeper understanding of language by associating it with perceptions and actions in real-world scenarios. Its aim is to establish correspondences between language and the physical world within multimodal data, thereby enhancing the interpretability and generalization capabilities of language models. Research in this area has significant application value and can drive advancements in human-computer interaction, robot navigation, and intelligent assistant systems.