AINeutralarXiv – CS AI · 10h ago6/10
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Words as Difference Makers: How Large Language Models Determine Causal Structure in Text
A new arXiv paper argues that Large Language Models learn causal structure through a difference-making logic called variational induction, rather than through traditional causal inference frameworks like Pearl's interventionism. The research analyzes how LLM architectural features like token embeddings and self-attention implement this logic by identifying which word variations influence text predictions.