@inproceedings{sil-etal-2023-primeqa,
    title = "{P}rime{QA}: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development",
    author = "Sil, Avi  and
      Sen, Jaydeep  and
      Iyer, Bhavani  and
      Franz, Martin  and
      Fadnis, Kshitij  and
      Bornea, Mihaela  and
      Rosenthal, Sara  and
      McCarley, Scott  and
      Zhang, Rong  and
      Kumar, Vishwajeet  and
      Li, Yulong  and
      Sultan, Md Arafat  and
      Bhat, Riyaz  and
      Bross, Juergen  and
      Florian, Radu  and
      Roukos, Salim",
    editor = "Bollegala, Danushka  and
      Huang, Ruihong  and
      Ritter, Alan",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-demo.5",
    doi = "10.18653/v1/2023.acl-demo.5",
    pages = "51--62",
    abstract = "The field of Question Answering (QA) has made remarkable progress in recent years, thanks to the advent of large pre-trained language models, newer realistic benchmark datasets with leaderboards, and novel algorithms for key components such as retrievers and readers. In this paper, we introduce PrimeQA: a one-stop and open-source QA repository with an aim to democratize QA research and facilitate easy replication of state-of-the-art (SOTA) QA methods. PrimeQA supports core QA functionalities like retrieval and reading comprehension as well as auxiliary capabilities such as question generation. It has been designed as an end-to-end toolkit for various use cases: building front-end applications, replicating SOTA methods on public benchmarks, and expanding pre-existing methods. PrimeQA is available at: \url{https://github.com/primeqa}.",
}

The field of Question Answering (QA) has made remarkable progress in recent years, thanks to the advent of large pre-trained language models, newer realistic benchmark datasets with leaderboards, and novel algorithms for key components such as retrievers and readers. In this paper, we introduce PrimeQA: a one-stop and open-source QA repository with an aim to democratize QA research and facilitate easy replication of state-of-the-art (SOTA) QA methods. PrimeQA supports core QA functionalities like retrieval and reading comprehension as well as auxiliary capabilities such as question generation. It has been designed as an end-to-end toolkit for various use cases: building front-end applications, replicating SOTA methods on public benchmarks, and expanding pre-existing methods. PrimeQA is available at: \url{https://github.com/primeqa}.
Sil, Avi Sen, Jaydeep Iyer, Bhavani Franz, Martin Fadnis, Kshitij Bornea, Mihaela Rosenthal, Sara McCarley, Scott Zhang, Rong Kumar, Vishwajeet Li, Yulong Sultan, Md Arafat Bhat, Riyaz Bross, Juergen Florian, Radu Roukos, Salim
PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development