activity
20242026
most citedTowards Universal Soccer Video Understanding

1 citations · 1 across the 11 of their papers we have counts for

collaborators
Showing cs.AIShow all

5 papers · 1 filter

cs.AI2026

WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting

Zhaokai Wang, Tianlin Gui, Jiayuan Rao +3

Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear prediction before the answer is available…

cs.AI2026

BasketEvent: Understanding Who Did What and When in Basketball Videos

Yu Zhang, Jiayuan Rao, Haoning Wu +1

Comprehensive basketball video understanding requires resolving not only what event occurs, but also who is responsible and when the key evidence appears. However, exist- ing metho…

cs.AI2026

SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing

Zi Meng, Wanli Song, Yi Hu +2

Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widely adopted in soccer refereei…

cs.AI2026

GenTac: Generative Modeling and Forecasting of Soccer Tactics

Jiayuan Rao, Tianlin Gui, Haoning Wu +2

Modeling open-play soccer tactics is a formidable challenge due to the stochastic, multi-agent nature of the game. Existing computational approaches typically produce single, deter…

cs.AI2025

STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions

Junjie Fan, Hongye Zhao, Linduo Wei +5

Recent adaptations of Large Language Models (LLMs) for time series forecasting often fail to effectively enhance information for raw series, leaving LLM reasoning capabilities unde…