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    <abstract>This paper provides an overview of the Shared Task RIRAG-2025, which focused on advancing the field of Regulatory Information Retrieval and Answer Generation (RIRAG). The task was designed to evaluate methods for answering regulatory questions using the ObliQA dataset. This paper summarizes the shared task, participants’ methods, and the results achieved by various teams.</abstract>
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%0 Conference Proceedings
%T Shared Task RIRAG-2025: Regulatory Information Retrieval and Answer Generation
%A Gokhan, Tuba
%A Wang, Kexin
%A Gurevych, Iryna
%A Briscoe, Ted
%Y Gokhan, Tuba
%Y Wang, Kexin
%Y Gurevych, Iryna
%Y Briscoe, Ted
%S Proceedings of the 1st Regulatory NLP Workshop (RegNLP 2025)
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F gokhan-etal-2025-shared
%X This paper provides an overview of the Shared Task RIRAG-2025, which focused on advancing the field of Regulatory Information Retrieval and Answer Generation (RIRAG). The task was designed to evaluate methods for answering regulatory questions using the ObliQA dataset. This paper summarizes the shared task, participants’ methods, and the results achieved by various teams.
%U https://aclanthology.org/2025.regnlp-1.1/
%P 1-4

Markdown (Informal)

[Shared Task RIRAG-2025: Regulatory Information Retrieval and Answer Generation](https://aclanthology.org/2025.regnlp-1.1/) (Gokhan et al., RegNLP 2025)

• Shared Task RIRAG-2025: Regulatory Information Retrieval and Answer Generation (Gokhan et al., RegNLP 2025)

ACL

• Tuba Gokhan, Kexin Wang, Iryna Gurevych, and Ted Briscoe. 2025. Shared Task RIRAG-2025: Regulatory Information Retrieval and Answer Generation. In Proceedings of the 1st Regulatory NLP Workshop (RegNLP 2025), pages 1–4, Abu Dhabi, UAE. Association for Computational Linguistics.