AINeutralarXiv – CS AI · 14h ago6/10
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CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists
Researchers introduce CausaLab, a benchmarking environment that tests whether LLM agents can both solve causal discovery problems and accurately recover the underlying causal mechanisms. Experiments reveal a significant gap between prediction accuracy (92%) and structural causal model recovery (0.471 F1 score), exposing limitations in current AI systems' ability to perform rigorous scientific reasoning.
🧠 GPT-5