In shared spaces, motorized and non-motorized road users share the same space with equal priority. Their movements are not regulated by traffic rules, hence they interact more frequently to negotiate priority over the shared space. To estimate the safeness and efficiency of shared spaces, reproducing the traffic behavior in such traffic places is important. In this paper, we consider and combine different levels of interaction between pedestrians and cars in shared space environments. Our proposed model consists of three layers: a layer to plan trajectories of road users; a force-based modeling layer to reproduce free flow movement and simple interactions; and a game-theoretic decision layer to handle complex situations where road users need to make a decision over different alternatives. We validate our model by simulating scenarios involving various interactions between pedestrians and cars and also car-to-car interaction. The results indicate that simulated behaviors match observed behaviors well.
3DTTNet: Multimodal Fusion-Based 3D Traversable Terrain Modeling for Off-Road Environments
Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen（深圳汽车研究院，北京理工大学，深圳）；School of Mechanical Engineering, Beijing Institute of Technology, Beijing（机械工程学院，北京理工大学，北京）；Research Center for Intelligent Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing（智能计算系统研究中心，计算技术研究所，中国科学院，北京）
Seeing with You: Perception-Reasoning Coevolution for Multimodal Reasoning
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学高瓴人工智能学院）；Zhejiang University（浙江大学）
Warned alike, AI agents avoid the less-crowded road while people take it
Research Center for Advanced Science and Technology, The University of Tokyo（东京大学先进科学技术研究中心）；Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo（东京大学工学部航空航天工程系）
研究发现，共享预测警告会使 AI 智能体群体过度规避某条路，导致集体效率下降，而人类则相反；评估需关注群体行为和成本分配。
V-SenseDrive: A Privacy-Preserving Road Video and In-Vehicle Sensor Fusion Framework for Road Safety & Driver Behaviour Modelling
School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST)（电气工程与计算机科学学院（SEECS），国立科学与技术大学（NUST））
DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data
IUCT-Oncopole Institut Claudius Regaud（克劳迪乌斯·雷戈德研究所肿瘤学中心）；IRT Saint Exupéry（圣埃克苏佩里技术研究院）；INSERM UMR 1037, Cancer Research Center of Toulouse (CRCT)（法国国家健康与医学研究院UMR 1037，图卢兹癌症研究中心）
Overview of the NLPCC 2026 Shared Task 1: Difficulty-Aware Multilingual and Multimodal Medical Instructional Video Understanding Evaluation
School of Computer Science and Technology, Beijing Institute of Technology（北京理工大学计算机科学与工程学院）；Department of Computing, The Hong Kong Polytechnic University（香港理工大学计算学系）；Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Southwest Jiaotong University（西南交通大学）；Microsoft Research Asia（微软亚洲研究院）；Southwestern University of Finance and Economics（西南财经大学）；Ocean University of China（中国海洋大学）；Tencent（腾讯）
Texas A&M University（德克萨斯农工大学）；Qatar Computing Research Institute（卡塔尔计算研究所）；Birzeit University（比尔宰特大学）；Hamad Bin Khalifa University（哈马德·本·哈利法大学）；University of Toronto（多伦多大学）
Multimodal Medical Image Binding via Shared Text Embeddings
The Hong Kong Polytechnic University（香港理工大学）；Emory University（埃默里大学）；The University of Hong Kong（香港大学）；University of Illinois Chicago（伊利诺伊大学芝加哥分校）；University of Science and Technology of China（中国科学技术大学）；Shanghai AI Laboratory（上海人工智能实验室）；Johns Hopkins University（约翰霍普金斯大学）
EviDep: Uncertainty-Aware Multimodal Depression Estimation via Disentangled Evidential Learning
School of Computer Science and Technology, University of Science and Technology of China（中国科学技术大学计算机科学与技术学院）；School of Computer Science and Information Engineering, Hefei University of Technology（合肥工业大学计算机科学与信息工程学院）；Department of Psychiatry, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China（中国科学技术大学附属第一医院精神科，生命科学与医学学院）
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection
School of Computer Science and Engineering, Beihang University（北京航空航天大学计算机科学与工程学院）；School of Vehicle and Mobility, Tsinghua University（清华大学车辆与 Mobility 学院）
