3 citations · 6 across the 11 of their papers we have counts for
5 papers · 1 filter
FACTS: Fine-Grained Action Classification for Tactical Sports
Christopher Lai, Jason Mo, Haotian Xia +1
Classifying fine-grained actions in fast-paced, close-combat sports such as fencing and boxing presents unique challenges due to the complexity, speed, and nuance of movements. Tra…
SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
Haotian Xia, Zhengbang Yang, Junbo Zou +10
Multimodal Large Language Models (MLLMs) are advancing the ability to reason about complex sports scenarios by integrating textual and visual information. To comprehensively evalua…
Sports Intelligence: Assessing the Sports Understanding Capabilities of Language Models through Question Answering from Text to Video
Zhengbang Yang, Haotian Xia, Jingxi Li +3
Understanding sports is crucial for the advancement of Natural Language Processing (NLP) due to its intricate and dynamic nature. Reasoning over complex sports scenarios has posed…
Language and Multimodal Models in Sports: A Survey of Datasets and Applications
Haotian Xia, Zhengbang Yang, Yun Zhao +7
Recent integration of Natural Language Processing (NLP) and multimodal models has advanced the field of sports analytics. This survey presents a comprehensive review of the dataset…
SportQA: A Benchmark for Sports Understanding in Large Language Models
Haotian Xia, Zhengbang Yang, Yuqing Wang +7
A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP). This holds particular significance in the…