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Humanities scholars commonly provide evidence for claims that they make abouta work of literature (e.g., a novel) in the form of quotations from the work.We collect a large-scale dataset (RELiC) of 78K literary quotations andsurrounding critical analysis and use it to formulate the novel task ofliterary evidence retrieval, in which models are given an excerpt of literaryanalysis surrounding a masked quotation and asked to retrieve the quotedpassage from the set of all passages in the work. Solving this retrieval taskrequires a deep understanding of complex literary and linguistic phenomena,which proves challenging to methods that overwhelmingly rely on lexical andsemantic similarity matching. We implement a RoBERTa-based dense passageretriever for this task that outperforms existing pretrained informationretrieval baselines; however, experiments and analysis by human domain expertsindicate that there is substantial room for improvement over our denseretriever.

RELIC: Retrieving Evidence for Literary Claims