LLM agents can resolve scientific questions more effectively by scoring experiments based on how evidence redistributes belief across competing explanations, rather than just testing whether a single hypothesis is true or false.
This paper introduces Contrastive Discovery, a method for LLM agents to conduct scientific research more effectively by evaluating multiple competing explanations simultaneously rather than testing single hypotheses.