Researchers propose a method for multiple large language models to collaborate by interleaving their generations at the token level, optimizing the decision of which LLM should generate next.
Why it’s noteworthy: The approach outlines a future in which AI systems can work in concord, maximizing their strengths to deliver more nuanced and accurate outputs. It signals the possibility of more adaptable and intelligent systems capable of tapping specialized knowledge seamlessly to address complex problems.