9 papers
ProtoAct: Turning Wet-Lab Protocols into Embodied Robotic Actions
Zhe Liu, Jiaming Gu, Zhaohui Du +7
Biological wet-lab protocols are written for trained researchers and often leave routine operations, state-dependent conditions, and contextual parameters implicit, making them dif…
BioVLN: A Simulation Platform for Visual Language Navigation in Biomedical Laboratories
Zhe Liu, Quan Lu, Zhaohui Du +7
The paper presents BioVLN, a simulation platform that enables visual‑language navigation agents to safely approach biomedical laboratory instruments by modeling each instrument wit…
Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics
Zhe Liu, Huanbo Jin, Zhaohui Du +10
Pipette is an embodied simulation platform that provides open-source wet‑lab assets, a benchmark of 12 robotic tasks, and a data‑efficient augmentation pipeline to turn a few human…
ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI
Brain Team, Ziyang Gong, Haoming Gu +28
Embodied AI is moving from isolated perception or action modules toward physical agents that understand, plan under goals, act through robot bodies, monitor progress, and improve f…
IR-SIM: A Lightweight Skill-Native Simulator for Navigation, Learning, and Benchmarking
Ruihua Han, Shuai Wang, Chengyang Li +8
Simulation plays a key role in automated robotics research supported by large language models (LLMs). However, existing simulators often require custom code or complex interfaces,…
Muse Spark Safety & Preparedness Report
Cristina Menghini, Peter Ney, Hamza Kwisaba +117
Muse Spark is the latest large language model developed by Meta. In this report, we first present evaluations for catastrophic risk domains under Meta's Advanced AI Scaling Framewo…