New paper warns that LLM-generated covariates can break statistical inference

PtrPomorski · x · 2026-07-25

• The paper, “Inference with AI-Generated Covariates,” studies the risks of using LLM-generated features as observed covariates in downstream inference.
• It argues that input-dependent errors such as hallucination and look-ahead bias can invalidate inference, even after moment-level corrections.
• The proposed AI-PI framework combines bias correction, adaptive weighting across model-prompt pairs, and careful calibration-set design.
• The paper reports better statistical validity and tighter confidence intervals than naive LLM regression or simpler debiasing approaches, including an empirical news-sentiment / stock-returns study.

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