@inproceedings{xu-etal-2026-survey,
title = "A Survey of Large Models in Sports",
author = "Xu, Yichen and
Ma, Jianzhe and
Wang, Chuhan and
Cao, Zhonghao and
Chen, Liangyu and
Wang, Wenxuan and
Jin, Qin",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-acl.1851/",
pages = "37154--37189",
ISBN = "979-8-89176-395-1",
abstract = "Sports have witnessed growing global enthusiasm in recent years, serving as a vital force for physical health, cultural exchange, social connection, and economic growth. The rapid advancement of large models, particularly (multimodal) large language models (M)LLMs, has demonstrated transformative potential to reshape sports understanding, analysis, and interaction across diverse domains. This paper presents a comprehensive survey of large models in sports, including (i) an overview of tasks and applications across different participant groups; (ii) a detailed analysis of sports-related datasets and benchmarks; and (iii) a critical discussion of current challenges and future directions. Our goal is to establish a foundation for advancing research and practical development of large-model-driven sports intelligence. An open-source GitHub repository is maintained at: https://github.com/Road2Redemption/Awesome{\_}Large{\_}Models{\_}In{\_}Sports1."
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%0 Conference Proceedings
%T A Survey of Large Models in Sports
%A Xu, Yichen
%A Ma, Jianzhe
%A Wang, Chuhan
%A Cao, Zhonghao
%A Chen, Liangyu
%A Wang, Wenxuan
%A Jin, Qin
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Findings of the Association for Computational Linguistics: ACL 2026
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-395-1
%F xu-etal-2026-survey
%X Sports have witnessed growing global enthusiasm in recent years, serving as a vital force for physical health, cultural exchange, social connection, and economic growth. The rapid advancement of large models, particularly (multimodal) large language models (M)LLMs, has demonstrated transformative potential to reshape sports understanding, analysis, and interaction across diverse domains. This paper presents a comprehensive survey of large models in sports, including (i) an overview of tasks and applications across different participant groups; (ii) a detailed analysis of sports-related datasets and benchmarks; and (iii) a critical discussion of current challenges and future directions. Our goal is to establish a foundation for advancing research and practical development of large-model-driven sports intelligence. An open-source GitHub repository is maintained at: https://github.com/Road2Redemption/Awesome_Large_Models_In_Sports1.
%U https://aclanthology.org/2026.findings-acl.1851/
%P 37154-37189
Markdown (Informal)
[A Survey of Large Models in Sports](https://aclanthology.org/2026.findings-acl.1851/) (Xu et al., Findings 2026)
ACL
- Yichen Xu, Jianzhe Ma, Chuhan Wang, Zhonghao Cao, Liangyu Chen, Wenxuan Wang, and Qin Jin. 2026. A Survey of Large Models in Sports. In Findings of the Association for Computational Linguistics: ACL 2026, pages 37154–37189, San Diego, California, United States. Association for Computational Linguistics.