Xinyi Xu

Fine-tuned robotic policies can be biased towards certain instruction factors, but a new bias-aware data strategy can significantly enhance their performance with fewer demonstrations.

Forget random sampling – this framework crafts targeted, multi-turn function-calling data that catapults smaller LLMs to state-of-the-art performance.