CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

Zi-Rong Li, Si-Yang Liu, Tian-Zuo Wang, Han-Jia Ye|September 10, 2026arXiv

Key Takeaway

No single causal discovery method generalizes across different benchmark types; evaluation results depend heavily on which test scenario you use, making diverse benchmarks essential for fair comparison.

Summary

CausalArena is a comprehensive benchmark for evaluating causal discovery methods—tools that learn cause-and-effect relationships from data. It addresses a critical problem: existing benchmarks use different test scenarios, making it hard to compare methods fairly.

evaluation reasoning data

Key Terms

causal-discovery structural-causal-model benchmark-generalization pretraining-evaluation-overlap