Scaling Discovery Requires Forgetting
Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are capable of discovering new ideas. There are different ways to scale automated research: let one agent iterate for longer, run several agents in parallel, or further let the parallel agents communicate and build on one another's candidates. However,…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
