LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures
Self-driving laboratories (SDLs) aim to automate the full experimental loop, from scientific decision-making to physical execution. Ideally, AI-generated plans could be carried out directly by robotic systems, but reliable automation remains difficult in complex, open-world laboratory environments, where experiments often involve fine-grained manipulation, long-horizon procedures, and substantial variation across tasks and setups. Humans therefore remain an important execution interface between AI-generated plans and physical experiments, creating a need for clear and effective human-facing experimental guidance. Because laboratory procedures are inherently visual, spatial, and dynamic, vide
| Authors | Yuming Fu, Weijia Wu, Jing Chen et al. |
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| Primary category | |
| Published | 29 September 2026 |
| Last updated at source | — |
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- CSU-JPG/LabInstructDataset
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