Entity · paper

Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?

paperactivehuman-adults-and-llms-as-scientists-who-benefits-from-active-exploration--7bb1eb8c·1 events·first seen Jun 5, 2026

Aliases: Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?

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Recent events (1)

4arXiv · cs.CL·Jun 5, 2026·source ↗

Study compares human and LLM active causal reasoning, finding LLMs less efficient but near human-level on conjunctive rules

A new arXiv paper investigates whether active exploration reduces the 'conjunctive handicap' in causal learning, using a blicket detector task with adult participants who could freely intervene to identify causal objects. Results show active exploration substantially improves human conjunctive causal reasoning, though conjunctive rules still require more tests than disjunctive ones. State-of-the-art LLMs approach human-level hypothesis inference accuracy but show less efficient exploration strategies and similar conjunctive-disjunctive performance gaps, raising questions about the nature of LLM causal reasoning.

Evaluation and Benchmarking Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?