Laboratory automation has made remarkable progress through robotic platforms and AI-driven scientific reasoning. However, many laboratory operations (e.g., solid--solid transfer) remain inherently dynamic and require real-time adaptation to different materials and experimental conditions. Such precision-critical manipulations are difficult to standardize, motivating the use of humanoid robots with dexterous hands. Despite this opportunity, no existing benchmark evaluates humanoid manipulation in precision-critical laboratory environments. We present Labimus, to our knowledge, the first benchmark for humanoid dexterous manipulation in organic chemistry laboratories. Labimus reconstructs over 30 functionally faithful assets from real organic chemistry workstations through real-to-sim modeling, collectively covering the core operations of routine organic chemistry experiments. The benchmark integrates articulated laboratory instruments, particle-based powder physics, and closed-loop instrument readouts, enabling a complete manipulation-to-measurement pipeline. It further defines six atomic operations and a seven-step solid-weighing workflow derived from real laboratory standard operating procedures. We introduce a precision-aware evaluation protocol designed to jointly measure task completion, experimental precision, and long-horizon execution. We benchmark three representative policies under procedural layouts and environmental perturbations. Results reveal a precision gap: policies that successfully complete laboratory tasks can still fail to satisfy the quantitative tolerances required by experimental protocols. Our benchmark exposes a fundamental disconnect between task completion and experimental validity, providing a new testbed for developing reliable humanoid robots for scientific laboratories.
HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
Fudan University（复旦大学）；Institute of Artificial Intelligence (TeleAI), China Telecom（人工智能研究所（TeleAI），中国电信）；University of Science and Technology of China（中国科学技术大学）；East China University of Science and Technology（东华大学）
Ulsan National Institute of Science and Technology（蔚山国立科学技术院）
With the advance in robotic hardware and intelligent software, humanoid robot plays an important role in various tasks including service for human assistance and heavy job for hazardous industry. Recent advances in task learning enable humanoid robots to conduct dexterous manipulation tasks such as grasping objects and assembling parts of furniture. Operating objects without physical movements is an even more challenging task for humanoid robot because effects of actions may not be clearly seen in the physical configuration space and meaningful actions could be very complex in a long time hori…
Blind Dexterity: Whole-Body Humanoid Manipulation via Pure Proprioception
TU Darmstadt（达姆施塔特工业大学）；German Research Center for AI (DFKI)（德国人工智能研究中心）；Tongji University（同济大学）；Shanghai Research Institute for Autonomous Intelligent Systems（上海自主智能系统研究院）；Robotics Institute Germany（德国机器人研究所）
Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation
Embodied AI and Robotics (AIR) Lab, New York University, New York, USA and NYUAD Center for Artificial Intelligence and Robotics, New York University Abu Dhabi, Abu Dhabi, UAE（纽约大学Embodied AI和机器人实验室及纽约大学阿布扎赫尔人工智能与机器人中心）；Harvard AI and Robotics Lab, Harvard University, Boston, USA（哈佛大学人工智能与机器人实验室）；Department of Computer Science, University College London, London, UK（伦敦大学学院计算机科学系）；Department of Computer Science, University of Liverpool, UK（利物浦大学计算机科学系）；NYUAD Center for Artificial Intelligence and Robotics, New York University Abu Dhabi, Abu Dhabi, UAE（纽约大学阿布扎赫尔人工智能与机器人中心）
mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity
mimic robotics；ETH AI Center, ETH Zurich（ETH人工智能中心，ETH Zurich）；Soft Robotics Lab, Dept. of Mechanical and Process Engineering, ETH Zurich（软机器人实验室，机械与过程工程系，ETH Zurich）；Institute of Neuroinformatics, ETH Zurich and University of Zurich（神经信息研究所，ETH Zurich和苏黎世大学）
MSK-Bench: Benchmarking Full-Body Musculoskeletal Motor Control Across Tasks, Control Paradigms, and Physiological Metrics
Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院）；The University of Hong Kong (HKU)（香港大学）；Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University（清华大学交叉信息研究院）；School of Aerospace Engineering, Tsinghua University（清华大学航天航空学院）；Peking University (PKU)（北京大学）
Kinematics-Aware Multi-Policy Reinforcement Learning for Force-Capable Humanoid Loco-Manipulation
the Robot and Artificial Intellifence Lab, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China（机器人与人工智能实验室，电子与信息工程学院，同济大学，上海）；State Key Laboratory of Autonomous Intelligent Unmanned System(Tongji University), Shanghai, China（自主智能无人系统国家重点实验室（同济大学），上海）
X2-N: A Transformable Wheel-legged Humanoid Robot with Dual-mode Locomotion and Manipulation
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（香港理工大学电子与计算机工程系）；X-lab Department, Agibot Innovation Company（阿吉博创新公司X实验室）
CycleManip: Enabling Cyclic Task Manipulation via Effective Historical Perception and Understanding
School of Computer Science and Engineering, Sun Yat-sen University（中山大学计算机科学与工程学院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Loop Area Institute（深圳河套学院）
