@inproceedings{agarwal-etal-2025-overview,
title = "Overview of the {P}er{A}ns{S}umm 2025 Shared Task on Perspective-aware Healthcare Answer Summarization",
author = "Agarwal, Siddhant and
Akhtar, Md. Shad and
Yadav, Shweta",
editor = "Ananiadou, Sophia and
Demner-Fushman, Dina and
Gupta, Deepak and
Thompson, Paul",
booktitle = "Proceedings of the Second Workshop on Patient-Oriented Language Processing (CL4Health)",
month = may,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.cl4health-1.41/",
doi = "10.18653/v1/2025.cl4health-1.41",
pages = "445--455",
ISBN = "979-8-89176-238-1",
abstract = "This paper presents an overview of the Perspective-aware Answer Summarization (PerAnsSumm) Shared Task on summarizing healthcare answers in Community Question Answering forums hosted at the CL4Health Workshop at NAACL 2025. In this shared task, we approach healthcare answer summarization with two subtasks: (a) perspective span identification and classification and (b) perspective-based answer summarization (summaries focused on one of the perspective classes). Wedefine a benchmarking setup for comprehensive evaluation of predicted spans and generated summaries. We encouraged participants to explore novel solutions to the proposed problem and received high interest in the task with 23 participating teams and 155 submissions. This paper describes the task objectives, the dataset, the evaluation metrics and our findings. We share the results of the novel approaches adopted by task participants, especially emphasizing the applicability of Large Language Models in this perspective-based answer summarization task."
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<abstract>This paper presents an overview of the Perspective-aware Answer Summarization (PerAnsSumm) Shared Task on summarizing healthcare answers in Community Question Answering forums hosted at the CL4Health Workshop at NAACL 2025. In this shared task, we approach healthcare answer summarization with two subtasks: (a) perspective span identification and classification and (b) perspective-based answer summarization (summaries focused on one of the perspective classes). Wedefine a benchmarking setup for comprehensive evaluation of predicted spans and generated summaries. We encouraged participants to explore novel solutions to the proposed problem and received high interest in the task with 23 participating teams and 155 submissions. This paper describes the task objectives, the dataset, the evaluation metrics and our findings. We share the results of the novel approaches adopted by task participants, especially emphasizing the applicability of Large Language Models in this perspective-based answer summarization task.</abstract>
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%0 Conference Proceedings
%T Overview of the PerAnsSumm 2025 Shared Task on Perspective-aware Healthcare Answer Summarization
%A Agarwal, Siddhant
%A Akhtar, Md. Shad
%A Yadav, Shweta
%Y Ananiadou, Sophia
%Y Demner-Fushman, Dina
%Y Gupta, Deepak
%Y Thompson, Paul
%S Proceedings of the Second Workshop on Patient-Oriented Language Processing (CL4Health)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-238-1
%F agarwal-etal-2025-overview
%X This paper presents an overview of the Perspective-aware Answer Summarization (PerAnsSumm) Shared Task on summarizing healthcare answers in Community Question Answering forums hosted at the CL4Health Workshop at NAACL 2025. In this shared task, we approach healthcare answer summarization with two subtasks: (a) perspective span identification and classification and (b) perspective-based answer summarization (summaries focused on one of the perspective classes). Wedefine a benchmarking setup for comprehensive evaluation of predicted spans and generated summaries. We encouraged participants to explore novel solutions to the proposed problem and received high interest in the task with 23 participating teams and 155 submissions. This paper describes the task objectives, the dataset, the evaluation metrics and our findings. We share the results of the novel approaches adopted by task participants, especially emphasizing the applicability of Large Language Models in this perspective-based answer summarization task.
%R 10.18653/v1/2025.cl4health-1.41
%U https://aclanthology.org/2025.cl4health-1.41/
%U https://doi.org/10.18653/v1/2025.cl4health-1.41
%P 445-455
Markdown (Informal)
[Overview of the PerAnsSumm 2025 Shared Task on Perspective-aware Healthcare Answer Summarization](https://aclanthology.org/2025.cl4health-1.41/) (Agarwal et al., CL4Health 2025)
ACL