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Testing Generalizability in Causal Inference
By basing simulations on real data, our method ensures more realistic evaluations, which is often missing in current work relying on simplified datasets.
A Critical Review of Causal Reasoning Benchmarks for Large Language Models
We hope this work will pave the way towards a general framework for the assessment of causal understanding in LLMs and the design of novel benchmarks.
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