AI RESEARCH
IV Co-Scientist: Multi-Agent LLM Framework for Causal Instrumental Variable Discovery
arXiv CS.AI
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ArXi:2602.07943v2 Announce Type: replace In the presence of confounding between an endogenous variable and the outcome, instrumental variables (IVs) are used to isolate the causal effect of the endogenous variable. Identifying valid instruments requires interdisciplinary knowledge, creativity, and contextual understanding, making it a non-trivial task. In this paper, we investigate whether large language models (LLMs) can aid in this task. We perform a two-stage evaluation framework.