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ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds

Paper recorded by Signals 4 on 2026-09-24 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-24 on arXiv · recorded by Signals 4 on 2026-09-25

Category: cs.AI · 人工智能 · first seen 2026-09-25

Abstract

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 fro

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#14 most recent of 400 cs.AI papers we have recorded · ↑ newer: A Living Benchmark for Information Retrieval from Electronic Health Re · ↓ older: SAGE: Mitigating Long-Horizon Reasoning Biases via Topological Guidanc
Cite this page: ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds: the #14 most recent of 400 cs.AI papers we have recorded (as of 2026-09-24). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/explorationbench-measuring-ai-systems-exploration-in-verifiable-alien-worlds.html
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