12 papers
A Survey of Large Models in Sports
Yichen Xu, Jianzhe Ma, Chuhan Wang +4
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…
From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMs
Jiawei Qiu, Yichen Xu, Jianzhe Ma +5
Timely anticipation of physical hazards is essential for real-world safety, yet existing MLLM evaluations focus on harmful content or general risks, leaving proactive physical haza…
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…
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…
Mem-PAL: Towards Memory-based Personalized Dialogue Assistants for Long-term User-Agent Interaction
Zhaopei Huang, Qifeng Dai, Guozheng Wu +7
With the rise of smart personal devices, service-oriented human-agent interactions have become increasingly prevalent. This trend highlights the need for personalized dialogue assi…
ChartEditor: A Reinforcement Learning Framework for Robust Chart Editing
Liangyu Chen, Yichen Xu, Jianzhe Ma +5
Chart editing reduces manual effort in visualization design. Typical benchmarks limited in data diversity and assume access to complete chart code, which is seldom in real-world sc…
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…
ChartM: Benchmarking Chart Editing with Multimodal Instructions
Donglu Yang, Liang Zhang, Zihao Yue +4
Charts are a fundamental visualization format widely used in data analysis across research and industry. While enabling users to edit charts based on high-level intentions is of gr…
POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering
Yichen Xu, Liangyu Chen, Liang Zhang +3
Charts are a universally adopted medium for data communication, yet existing chart understanding benchmarks are overwhelmingly English-centric, limiting their accessibility and rel…
A Survey of Deep Learning for Geometry Problem Solving
Jianzhe Ma, Wenxuan Wang, Qin Jin
Geometry problem solving, a crucial aspect of mathematical reasoning, is vital across various domains, including education, the assessment of AI's mathematical abilities, and multi…
IntentionESC: An Intention-Centered Framework for Enhancing Emotional Support in Dialogue Systems
Xinjie Zhang, Wenxuan Wang, Qin Jin
In emotional support conversations, unclear intentions can lead supporters to employ inappropriate strategies, inadvertently imposing their expectations or solutions on the seeker.…
Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
Ye Wang, Ziheng Wang, Boshen Xu +14
Temporal Video Grounding (TVG), the task of locating specific video segments based on language queries, is a core challenge in long-form video understanding. While recent Large Vis…