RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents

Sayantan Adak, Animesh Mukherjee
2/17/2025
cs.CL

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Abstract

Inspirational quotes from famous individuals are often used to convey thoughts in news articles, essays, and everyday conversations. In this paper, we propose a novel context-based quote extraction system that aims to extract the most relevant quote from a long text. We formulate this quote extraction as an open domain question answering problem first by employing a vector-store based retriever and then applying a multi-task reader. We curate three context-based quote extraction datasets and introduce a novel multi-task framework RA-MTR that improves the state-of-the-art performance, achieving a maximum improvement of 5.08% in BoW F1-score.

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Cite this paper

@article{adak2025ramtr,
  title  = {RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents},
  author = {Sayantan Adak and Animesh Mukherjee},
  year   = {2025},
  eprint = {2502.12124},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.12124v1}
}

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