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cs.CV2026
EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports
Jianzhe Ma, Zhonghao Cao, Shangkui Chen +3
While video large language models (Video-LLMs) excel in understanding slow-paced, real-world egocentric videos, their capabilities in high-velocity, information-dense virtual envir…
cs.CV2026
RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees
Yichen Xu, Yuanhang Liu, Chuhan Wang +5
While Multimodal Large Language Models (MLLMs) excel at generic video understanding, their ability to support specialized, rule-grounded decision-making remains insufficiently expl…
cs.CV2025
UI-Ins: Enhancing GUI Grounding with Multi-Perspective Instruction-as-Reasoning
Liangyu Chen, Hanzhang Zhou, Chenglin Cai +10
GUI grounding, which maps natural-language instructions to actionable UI elements, is a core capability of GUI agents. Prior works largely treats instructions as a static proxy for…