MIND: Benchmarking Memory Consistency and Action Control in World Models
CSU-JPG, Central South University（中南大学）；National University of Singapore（新加坡国立大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Nanyang Technological University（南洋理工大学）
Yixuan Ye, Xuanyu Lu, Yuxin Jiang, Yuchao Gu, Rui Zhao, Qiwei Liang, Jiachun Pan, Fengda Zhang, Weijia Wu, Alex Jinpeng Wang
World models aim to understand, remember, and predict dynamic visual environments, yet a unified benchmark for evaluating their fundamental abilities remains lacking. To address this gap, we introduce MIND, the first open-domain closed-loop revisited benchmark for evaluating Memory consIstency and action coNtrol in worlD models. MIND contains 250 high-quality videos at 1080p and 24 FPS, including 100 (first-person) + 100 (third-person) video clips under a shared action space and 25 + 25 clips across varied action spaces covering eight diverse scenes. We design an efficient evaluation framework to measure two core abilities: memory consistency and action control, capturing temporal stability and contextual coherence across viewpoints. Furthermore, we design various action spaces, including different character movement speeds and camera rotation angles, to evaluate the action generalization capability across different action spaces under shared scenes. To facilitate future performance benchmarking on MIND, we introduce MIND-World, a novel interactive Video-to-World baseline. Extensive experiments demonstrate the completeness of MIND and reveal key challenges in current world models, including the difficulty of maintaining long-term memory consistency and generalizing across action spaces. Code: https://github.com/CSU-JPG/MIND.
Benchmarking Intra-Patient 3D Deformable Multimodal Image Registration
IMAG2, Institut IMAGINE, Université Paris Cité（IMAG2，IMAGINE研究所，巴黎西岱大学）；Replico SAS（Replico公司）；Université Paris Cité, Department of Pediatric Surgery, Hôpital Necker Enfants-Malades, Assistance Publique–Hôpitaux de Paris (AP-HP)（巴黎西岱大学，内克尔儿童医院小儿外科，巴黎公立医院集团）；Sorbonne Université, CNRS, LIP6（索邦大学，法国国家科学研究中心，LIP6）；LTCI, Télécom Paris, Institut Polytechnique de Paris（LTCI，巴黎电信，巴黎综合理工学院）
GUI-CC: Benchmarking Contextual Consistency of GUI World Models as Agent Environments
Yale University（耶鲁大学）；Zhejiang University（浙江大学）；China University of Geosciences（中国地质大学）；DAMO Academy, Alibaba Group（阿里巴巴达摩院）；Tongji University（同济大学）；University of California, San Diego（加利福尼亚大学圣迭戈分校）
MindWorldBench: Evaluating Mental-State-to-Behavior Reasoning in Image-to-Video Generation
Peking University（北京大学）；University of Science and Technology Beijing（北京科技大学）；City University of Hong Kong（香港城市大学）；Nanyang Technological University（南洋理工大学）
GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs
Xidian University（西安电子科技大学）；National University of Singapore（新加坡国立大学）；University of Electronic Science and Technology of China（电子科技大学）；University of Science and Technology of China（中国科学技术大学）
OpenECG: Benchmarking ECG Foundation Models with Public 1.2 Million Records
The First Affiliated Hospital, Jiangxi Medical College, Nanchang University（南昌大学江西医学院第一附属医院）；Nanchang University（南昌大学）；Georgia Institution of Technology（佐治亚理工学院）
Mind the Context: Attention-Guided Weak-to-Strong Consistency for Enhanced Semi-Supervised Medical Image Segmentation
College of Engineering Huazhong Agricultural University Wuhan, China（华中农业大学工程学院）；College of Informatics Huazhong Agricultural University Wuhan, China（华中农业大学信息学院）
Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection
School of Artificial Intelligence and Robotics, Hunan University（湖南大学人工智能与机器人学院）；National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University（湖南大学机器人视觉感知与控制技术国家工程研究中心）
Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络与信息安全学院）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；School of Computer Science and Technology, University of Chinese Academy of Sciences（中国科学院大学计算机科学与技术学院）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）
Benchmarking Attention Mechanisms and Consistency Regularization Semi-Supervised Learning for Post-Flood Building Damage Assessment in Satellite Images
