RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees
Fuente:
arXiv
Guardado en:
| Autores principales: | Xu, Yichen, Liu, Yuanhang, Wang, Chuhan, Zhao, Zihan, luo, jinghan, Ma, Jianzhe, Wang, Wenxuan, Jin, Qin |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
A Survey of Deep Learning for Geometry Problem Solving
por: Ma, Jianzhe, et al.
Publicado: (2025)
por: Ma, Jianzhe, et al.
Publicado: (2025)
POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering
por: Xu, Yichen, et al.
Publicado: (2025)
por: Xu, Yichen, et al.
Publicado: (2025)
EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports
por: Ma, Jianzhe, et al.
Publicado: (2026)
por: Ma, Jianzhe, et al.
Publicado: (2026)
Referee: Reference-aware Audiovisual Deepfake Detection
por: Boo, Hyemin, et al.
Publicado: (2025)
por: Boo, Hyemin, et al.
Publicado: (2025)
Implicit Biases in Refereeing: Lessons from NBA Referees
por: Pelechrinis, Konstantinos
Publicado: (2022)
por: Pelechrinis, Konstantinos
Publicado: (2022)
Towards AI-Powered Video Assistant Referee System (VARS) for Association Football
por: Held, Jan, et al.
Publicado: (2024)
por: Held, Jan, et al.
Publicado: (2024)
MMDuet2: Enhancing Proactive Interaction of Video MLLMs with Multi-Turn Reinforcement Learning
por: Wang, Yueqian, et al.
Publicado: (2025)
por: Wang, Yueqian, et al.
Publicado: (2025)
VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views
por: Held, Jan, et al.
Publicado: (2023)
por: Held, Jan, et al.
Publicado: (2023)
X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model
por: Held, Jan, et al.
Publicado: (2024)
por: Held, Jan, et al.
Publicado: (2024)
ChartEditor: A Reinforcement Learning Framework for Robust Chart Editing
por: Chen, Liangyu, et al.
Publicado: (2025)
por: Chen, Liangyu, et al.
Publicado: (2025)
Unhackable Temporal Rewarding for Scalable Video MLLMs
por: Yu, En, et al.
Publicado: (2025)
por: Yu, En, et al.
Publicado: (2025)
Exploring the Design Space of Visual Context Representation in Video MLLMs
por: Du, Yifan, et al.
Publicado: (2024)
por: Du, Yifan, et al.
Publicado: (2024)
AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
por: Wang, Junyang, et al.
Publicado: (2023)
por: Wang, Junyang, et al.
Publicado: (2023)
MileBench: Benchmarking MLLMs in Long Context
por: Song, Dingjie, et al.
Publicado: (2024)
por: Song, Dingjie, et al.
Publicado: (2024)
CameraBench: Benchmarking Visual Reasoning in MLLMs via Photography
por: Fang, I-Sheng, et al.
Publicado: (2025)
por: Fang, I-Sheng, et al.
Publicado: (2025)
SpatialViz-Bench: A Cognitively-Grounded Benchmark for Diagnosing Spatial Visualization in MLLMs
por: Wang, Siting, et al.
Publicado: (2025)
por: Wang, Siting, et al.
Publicado: (2025)
Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs
por: Yeh, Chun-Hsiao, et al.
Publicado: (2025)
por: Yeh, Chun-Hsiao, et al.
Publicado: (2025)
VIR-Bench: Evaluating Geospatial and Temporal Understanding of MLLMs via Travel Video Itinerary Reconstruction
por: Wang, Hao, et al.
Publicado: (2025)
por: Wang, Hao, et al.
Publicado: (2025)
VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning
por: Qi, Yukun, et al.
Publicado: (2025)
por: Qi, Yukun, et al.
Publicado: (2025)
Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee
por: Ansalone, Filippo, et al.
Publicado: (2024)
por: Ansalone, Filippo, et al.
Publicado: (2024)
Human Cognitive Benchmarks Reveal Foundational Visual Gaps in MLLMs
por: Huang, Jen-Tse, et al.
Publicado: (2025)
por: Huang, Jen-Tse, et al.
Publicado: (2025)
Can Multimodal Foundation Models Understand Schematic Diagrams? An Empirical Study on Information-Seeking QA over Scientific Papers
por: Zhao, Yilun, et al.
Publicado: (2025)
por: Zhao, Yilun, et al.
Publicado: (2025)
Cube Bench: A Benchmark for Spatial Visual Reasoning in MLLMs
por: Anand, Dhruv, et al.
Publicado: (2025)
por: Anand, Dhruv, et al.
Publicado: (2025)
STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?
por: Li, Yun, et al.
Publicado: (2025)
por: Li, Yun, et al.
Publicado: (2025)
AdaCodec: A Predictive Visual Code for Video MLLMs
por: Hou, Haowen, et al.
Publicado: (2026)
por: Hou, Haowen, et al.
Publicado: (2026)
Linking Perception, Confidence and Accuracy in MLLMs
por: Du, Yuetian, et al.
Publicado: (2026)
por: Du, Yuetian, et al.
Publicado: (2026)
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models
por: Diesendruck, Maurice, et al.
Publicado: (2024)
por: Diesendruck, Maurice, et al.
Publicado: (2024)
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
por: Wang, Fei, et al.
Publicado: (2024)
por: Wang, Fei, et al.
Publicado: (2024)
VideoScaffold: Elastic-Scale Visual Hierarchies for Streaming Video Understanding in MLLMs
por: Zheng, Naishan, et al.
Publicado: (2025)
por: Zheng, Naishan, et al.
Publicado: (2025)
Drawing the Line: Enhancing Trustworthiness of MLLMs Through the Power of Refusal
por: Wang, Yuhao, et al.
Publicado: (2024)
por: Wang, Yuhao, et al.
Publicado: (2024)
Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
por: Wang, Ye, et al.
Publicado: (2025)
por: Wang, Ye, et al.
Publicado: (2025)
VEFX-Bench: A Holistic Benchmark for Generic Video Editing and Visual Effects
por: Gao, Xiangbo, et al.
Publicado: (2026)
por: Gao, Xiangbo, et al.
Publicado: (2026)
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
por: Wu, Daiqing, et al.
Publicado: (2025)
por: Wu, Daiqing, et al.
Publicado: (2025)
TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding
por: Xu, Boshen, et al.
Publicado: (2025)
por: Xu, Boshen, et al.
Publicado: (2025)
Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs
por: Xu, Xiao, et al.
Publicado: (2025)
por: Xu, Xiao, et al.
Publicado: (2025)
The Power of Strong Linearizability: the Difficulty of Consistent Refereeing
por: Attiya, Hagit, et al.
Publicado: (2025)
por: Attiya, Hagit, et al.
Publicado: (2025)
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
por: Zhao, Yilun, et al.
Publicado: (2025)
por: Zhao, Yilun, et al.
Publicado: (2025)
IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs
por: Ma, David, et al.
Publicado: (2025)
por: Ma, David, et al.
Publicado: (2025)
VisBias: Measuring Explicit and Implicit Social Biases in Vision Language Models
por: Huang, Jen-tse, et al.
Publicado: (2025)
por: Huang, Jen-tse, et al.
Publicado: (2025)
VideoCoT: A Video Chain-of-Thought Dataset with Active Annotation Tool
por: Wang, Yan, et al.
Publicado: (2024)
por: Wang, Yan, et al.
Publicado: (2024)
Ejemplares similares
-
A Survey of Deep Learning for Geometry Problem Solving
por: Ma, Jianzhe, et al.
Publicado: (2025) -
POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering
por: Xu, Yichen, et al.
Publicado: (2025) -
EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports
por: Ma, Jianzhe, et al.
Publicado: (2026) -
Referee: Reference-aware Audiovisual Deepfake Detection
por: Boo, Hyemin, et al.
Publicado: (2025) -
Implicit Biases in Refereeing: Lessons from NBA Referees
por: Pelechrinis, Konstantinos
Publicado: (2022)