arXiv: cs.AI preprintsInternational11 November 2026
Contrastive Discovery: Open-Ended Scientific Discovery over Competing Explanations
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arXiv:2611.14514v1 Announce Type: new Abstract: LLM agents are increasingly used for open-ended, data-driven scientific discovery, yet most of them evaluate hypotheses pointwise, testing an empirical claim $h$ only against its complement $\neg h$. When evidence rejects $h$, the agent learns that one explanation is unlikely but not which alternative the evidence supports. To recover that alternative, we introduce Contrastive Discovery, which replaces the single hypothesis with a contrast set, a scientific question paired with mutually exclusive and collectively exhaustive competing explanations
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