SleuthBench: Benchmarking Statistical LLM Evaluation Using Tabular Hidden Signals
Evaluating statistical discovery by large language model (LLM) agents requires verifiable analytical ground truth. Establishing such ground truth for real-world datasets is costly, and prior knowledge of public datasets can influence agent responses. We introduce SLEUTHBENCH, a benchmark that addresses both problems by...
Jing-Yu Jia, Antoine Remond-Tiedrez, Aaron Alvarez et al.
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