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Resolving the contextual dependency is one of the most challenging tasks inthe Conversational system. Our submission to CAsT-2021 aimed to preserve thekey terms and the context in all subsequent turns and use classical Informationretrieval methods. It was aimed to pull as relevant documents as possible fromthe corpus. We have participated in automatic track and submitted two runs inthe CAsT-2021. Our submission has produced a mean NDCG@3 performance betterthan the median model.

IITD-DBAI: Multi-Stage Retrieval with Pseudo-Relevance Feedback and Query Reformulation