Don't Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments

Sara Salamat, Negar Arabzadeh, Amin Bigdeli, Shirin Seyedsalehi, Morteza Zihayat, Ebrahim Bagheri

Abstract: The Information Retrieval community has made strides in developing neural rankers, which have show strong retrieval effectiveness on large-scale gold standard datasets. The focus of existing neural rankers has primarily been on measuring the relevance of a document or passage to the user query. However, other considerations such as the convincingness of the content are not taken into account when retrieving content. We present a large gold standard dataset, referred to as CoRe, which focuses on enabling researchers to explore the integration of the concepts of convincingness and relevance to allow for the retrieval of relevant yet persuasive content. Through extensive experiments on this dataset, we report that there is a close association between convincingness and relevance that can have practical value in how convincing content are presented and retrieved in practice.