Two new research papers highlight significant issues with the evaluation of genomic foundation models. The first paper argues that current practices rely too heavily on anecdotal evidence and proposes a framework similar to clinical trials for more rigorous assessment. The second paper introduces GENEB, a comprehensive benchmark designed to allow for direct comparison of these models across various tasks and architectures, revealing that model rankings are unstable and often depend heavily on the specific task. AI
IMPACT Lack of standardized evaluation hinders progress in genomic AI; new benchmarks aim to provide clarity for model selection.
RANK_REASON Two papers propose new evaluation frameworks and benchmarks for genomic AI models.
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