  Computational Paninian Grammar model helps in decoding a natural language
expression as a series of modifier-modified relations and therefore facilitates
in identifying dependency relations closer to language (context) semantics
compared to the usual Stanford dependency relations. However, the importance of
this CPG dependency scheme has not been studied in the context of multi-modal
vision and language applications. At IIIT Hyderabad, we plan to perform a novel
study to explore the potential advantages and disadvantages of CPG framework in
a vision-language navigation task setting, a popular and challenging
multi-modal grounding task.
