Turiya at P erpective A rg2024: A Multilingual Argument Retriever and Reranker (2024)

Abstract: While general argument retrieval systems have significantly matured, multilingual argument retrieval in a socio-cultural setting is an overlooked problem. Advancements in such systems are imperative to enhance the inclusivity of society. The Perspective Argument Retrieval (PAR) task addresses these aspects and acknowledges their potential latent influence on argumentation. Here, we present a multilingual retrieval system for PAR that accounts for societal diversity during retrieval. Our approach couples a retriever and a re-ranker and spans multiple languages, thus factoring in diverse socio-cultural settings. The performance of our end-to-end system on three distinct test sets testify to its robustness.

## introduction given a query, argument retrieval @xcite @xcite generally involves retrieving a set of k-relevant arguments from a corpus. perspective argument retrieval (par) @xcite is an expansion and concerns factoring in the socio-cultural factors during retrieval. apart from the semantic features, it considers aspects such as persona, attitude, demographics, etc, during retrieval. such systems are imperative to expanding the reach of argumentation technologies @xcite among diverse socio-cultural groups. we tackle the following two scenarios of the par shared task: (i) baseline: given a query, retrieving the relevant arguments from a corpus. this scenario evaluates the general abilities of a system to retrieve relevant arguments. (ii) explicit: this extends the baseline task by explicitly adding socio-cultural information to the query and the corpus and limiting the relevant candidates to arguments from authors matching the corresponding socio-cultural background. this scenario tests if a retrieval system can consider socio-cultural properties when explicitly mentioned in the query and the candidates. the argument corpus comprises 26,335 arguments covering the 2019 swiss federal elections in german, french, and italian. each argument is enriched with eight socio-cultural properties and spans 45 political aspects. the queries are political issues and based on the x-stance dataset @xcite . the training queries span 35 political aspects, whereas the development set queries span the other 10 aspects. the final evaluation set comprises three secret test sets. ## proposed method our implemented architecture comprises a retriever and a re-ranker. figure 1 illustrates our architecture, which we explain in detail below. ## results we run our pipeline on the three official test sets and share the results for the baseline scenario in ## conclusion here, we present an end-to-end retrieval and ranking system capable of retrieving multilingual arguments to user queries while factoring in the sociocultural features. our implementation uses the original and english-translated text and implements an ensembled retriever and re-ranker to retrieve relevant documents. our retriever combines the semantic relatedness of embedding a similarity-based