From the 2 of 7 linked papers with an AI index.
7 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…
LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories
Baochang Ren, Xinjie Liu, Xi Chen +15
Scientific laboratories increasingly rely on AI systems to reason about experiments, but the physical act of doing science remains largely outside their reach. AI can help read lit…
Continual Visual Reinforcement Learning with A Life-Long World Model
Minting Pan, Wendong Zhang, Geng Chen +4
Learning physical dynamics in a series of non-stationary environments is a challenging but essential task for model-based reinforcement learning (MBRL) with visual inputs. It requi…
Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimization
Haochen Yuan, Minting Pan, Yunbo Wang +3
Reinforcement learning (RL) has shown significant promise for sequential portfolio optimization tasks, such as stock trading, where the objective is to maximize cumulative returns…