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Charles Doss

1 accepted papers

2026

Ice Cream Doesn’t Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference

ICLR 2026poster

Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains unclear whether large language models (LLMs) can handle rigorous and trustworthy \textit{statistical causal inference}. Current benchmarks usually involve…

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