- Srijan Bansal, Suraj Tripathi, Sumit Agarwal, Sireesh Gururaja, Aditya Srikanth Veerubhotla, Ritam Dutt, T. Mitamura, Eric Nyberg. 2022. R3 : Refined Retriever-Reader pipeline for Multidoc2dial. Abstract: In this paper, we present our submission to the DialDoc shared task based on the MultiDoc2Dial dataset. MultiDoc2Dial is a conversational question answering dataset that grounds dialogues in multiple documents. The task involves grounding a user’s query in a document followed by generating an appropriate response. We propose several improvements over the baseline’s retriever-reader architecture to aid in modeling goal-oriented dialogues grounded in multiple documents. Our proposed approach employs sparse representations for passage retrieval, a passage re-ranker, the fusion-in-decoder architecture for generation, and a curriculum learning training paradigm. Our approach shows a 12 point improvement in BLEU score compared to the baseline RAG model.
