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LLM development is flying blind by ignoring causal inference, leaving models vulnerable to confounding and distribution shifts throughout pretraining, alignment, and evaluation.
Unstable estimates in long-term treatment effect prediction? These orthogonal learners use custom overlap weights to improve robustness in low-overlap settings common in long-term outcomes.
