papers

Publications (7)

cs.CL2024

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…

cs.LG2024

VREN: Volleyball Rally Dataset with Expression Notation Language

Haotian Xia, Rhys Tracy, Yun Zhao +3

This research is intended to accomplish two goals: The first goal is to curate a large and information rich dataset that contains crucial and succinct summaries on the players' act…

cs.CV2023

Advanced Volleyball Stats for All Levels: Automatic Setting Tactic Detection and Classification with a Single Camera

Haotian Xia, Rhys Tracy, Yun Zhao +3

This paper presents PathFinder and PathFinderPlus, two novel end-to-end computer vision frameworks designed specifically for advanced setting strategy classification in volleyball…

cs.CV2026

SportR: A Benchmark for Multimodal Large Language Model Reasoning in Sports

Haotian Xia, Haonan Ge, Junbo Zou +16

Deeply understanding sports requires an intricate blend of fine-grained visual perception and rule-based reasoning - a challenge that pushes the limits of current multimodal models…

cs.CV2025

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…

cs.LG2023

Graph Encoding and Neural Network Approaches for Volleyball Analytics: From Game Outcome to Individual Play Predictions

Rhys Tracy, Haotian Xia, Alex Rasla +2

This research aims to improve the accuracy of complex volleyball predictions and provide more meaningful insights to coaches and players. We introduce a specialized graph encoding…