Toward Controlling Biology with Language: Offline Learning of Prompt-Conditioned
Overview
This research introduces a method to interface natural language with living matter by learning offline mappings between text prompts and electrical pulse interventions for xenobots. By re-tracking an archive of 155 recordings using two independent methods and replacing hand-made labels with a blind multimodal language model critic, the authors show that a prompt-to-intervention model can generalize to unseen instructions and bots. The approach establishes a calibrated interface for three controllable behaviors while explicitly identifying those it cannot control, without requiring new wet-lab experiments for each instruction.
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- arXiv Robotics — research abstractsSignalToward Controlling Biology with Language: Offline Learning of Prompt-Conditioned Interventions for Cells, Organoids, and Biobots
This research introduces a method to interface natural language with living matter by learning offline mappings between text prompts and electrical pulse interventions for xenobots. By re-tracking an archive of 155 recordings using two independent methods and replacing hand-made labels with a blind multimodal language model critic, the authors show that a prompt-to-intervention model can generalize to unseen instructions and bots. The approach establishes a calibrated interface for three controllable behaviors while explicitly identifying those it cannot control, without requiring new wet-lab experiments for each instruction.
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