The Base-Rate Effect on LLM Benchmark Performance: Disambiguating Test-Taking Strategies from Benchmark Performance
<|reference_start|>The Base-Rate Effect on LLM Benchmark Performance: Disambiguating Test-Taking Strategies from Benchmark Performance: Cloze testing is a common method for measuring the behavior of large language models on a number of benchmark tasks. Using the MMLU dataset, we show that the base-rate probability (BRP) differences across answer tokens are significant and affect task performance ie. guess A if uncertain. We find that counterfactual prompting does sufficiently mitigate the BRP effect. The BRP effect is found to have a similar effect to test taking strategies employed by humans leading to the conflation of task performance and test-taking ability. We propose the Nvr-X-MMLU task, a variation of MMLU, which helps to disambiguate test-taking ability from task performance and reports the latter.<|reference_end|>
@article{moore2024the,
    title={The Base-Rate Effect on LLM Benchmark Performance: Disambiguating
  Test-Taking Strategies from Benchmark Performance},
    author={Kyle Moore, Jesse Roberts, Thao Pham, Oseremhen Ewaleifoh, Doug Fisher},
    journal={arXiv preprint arXiv:2406.11634},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.11634},
    primaryClass={cs.CL cs.AI}
}