The Base-Rate Effect on LLM Benchmark Performance: Disambiguating Test-Taking Strategies from Benchmark Performance
Kyle T. Moore, Jesse Roberts, Thao Pham, Oseremhen Ewaleifoh, Douglas Fisher · 2024
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.