A Survey of Large Models in Sports
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Computer Science > Computation and Language
Title:A Survey of Large Models in Sports
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: this https URL.
| Comments: | 36 pages, 4 figures, 6 tables. Accepted to Findings of ACL 2026 |
| Subjects: | Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2608.14377 [cs.CL] |
| (or arXiv:2608.14377v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.14377
arXiv-issued DOI via DataCite (pending registration)
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| Related DOI: | https://doi.org/10.18653/v1/2026.findings-acl.1851
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