Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer explores Investigating the limitations of current AI models in abstract causal structure transfer, highlighting a reliance on environmental grounding over human-like analogical reasoning. in Causal Reasoning.
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/buildability/grounding-before-generalizing-how-ai-differs-from-humans-in-causal-transfer
Subject: Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer
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Receipt path
/buildability/grounding-before-generalizing-how-ai-differs-from-humans-in-causal-transfer
Paper ref
grounding-before-generalizing-how-ai-differs-from-humans-in-causal-transfer
arXiv id
2604.24062
Generated at
2026-04-28T15:20:53.813Z
Evidence freshness
fresh
Last verification
2026-04-28T15:20:53.813Z
Sources
3
References
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Coverage
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a9e54afbd0ccf64a66e0b69a14bcccefd54100c6821d7ac8f0200b0d2ff96c33
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This equation captures one of the core mathematical components of the system. (SD = 9.09, N = 80) to identify all three solutions. Gemini-
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This equation captures one of the core mathematical components of the system. N = 40; t(78) = −1.27, p = .207). In contrast, all models
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This equation captures one of the core mathematical components of the system. (SD = 9.53, N = 61; t(139) = 3.12, p = .002). DeepSeek-
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