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Causal graphs reveal how LLMs perceive concepts, transforming our understanding of model reasoning and interpretability.
LLMs like GPT-5 and Gemini-3 already "know" almost everything (95-98% factual encoding), but struggle to recall it, suggesting that future gains in factuality depend more on better memory retrieval than on simply scaling up.
