Lin Sun

UniFS achieves a remarkable 2.5% increase in success rate while slashing inference latency by over half, redefining efficiency in vision-language-action models.

Selective retrieval of external experience can significantly enhance task quality while minimizing costs, outperforming traditional global injection methods.

The organization of post-training reasoning data into a cohesive framework reveals crucial insights that could accelerate advancements in large reasoning models.