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CausalBench A Comprehensive Benchmark for Evaluating Causal Reasoning Capabilities of Large Language Models

<p>CausalBench is a comprehensive benchmark dataset designed to evaluate the causal reasoning capabilities of large language models. The primary uses of this dataset include, but are not limited to:</p> <p>- Testing the performance of large language models on causal reasoning tasks</p> <p>- Serving as a benchmark dataset for causal reasoning research</p> <p>- Improving and developing new causal reasoning algorithms and models</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4