SOURCE-LINKED INTELLIGENCE
ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds
Scientific discovery begins where known problems end. There, AI systems must engage in exploration: framing hypotheses, designing experiments, and iterating on the results. However, evaluating this ability is difficult: (1) how to verify whether a genuinely new hypothesis holds, and (2) how to determine whether a system has discovered it through exploration or merely recalled related knowledge from pre-training data. To this end, we introduce ExplorationBench, which turns the wicked problem of evaluating scientific exploration into a concrete and tractable framework built on verifiable Alien W
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:37:14.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.