While bureaucrats and the “concerned citizenry” panic about chatbots, LLMs are busy doing what they can’t — making us more productive. Here’s a figure Overleaf generated from LaTeX code that Gemini 2.5 Pro writes from my verbal (3 sentences) description of this NCM architecture!…
Nice! Yes, they are definitely useful here. Not sure what prompt you used, but I noticed latent U confounds all three variables, and the trained model will not accurately represent true interventional samples since they are non-identifiable in this graph. Perhaps an LLM mistake?
glad you noticed. that’s by intent, though; that’s how I asked. we can condition on a global confounder U, the study-unit variable, and identify an ITE, right? but, conventinally, all U_i=g_i(U) are sampled from independent distributions. If you have time next week,…
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