A 133M-parameter ensemble of fine-tuned mpnet and MiniLM encoders achieves 83.5% accuracy on a 200-task synthetic benchmark for robot skill prediction, beating several larger zero-shot LLMs.
Large Language Models For Robot Task Allocation,
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To Select or not to Select, that is the Question: Distilling Robot Skill Prediction into a Small Ensemble
A 133M-parameter ensemble of fine-tuned mpnet and MiniLM encoders achieves 83.5% accuracy on a 200-task synthetic benchmark for robot skill prediction, beating several larger zero-shot LLMs.