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This is a Experimental Study study.

October 9, 2025Open Access

Language Agents Mirror Human Causal Reasoning Biases. How Can We Help Them Think Like Scientists?

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Examination of causal reasoning biases in language models using the Blicket Test, suggesting improvements for scientific reasoning.

Language models show a persistent disjunctive bias in causal reasoning, resembling biases seen in adult humans.
In testing, performance declines in LMs as task complexity increases, revealing limitations in causal understanding.
Using the Blicket Test, the study highlights LMs' struggle with conjunction relationships compared to disjunctions.
A proposed test-time sampling method effectively reduces bias in LMs, improving their reasoning capabilities.

GX-Chen et al. (2025) studied this question.

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