Benchmarks as Microscopes: A Call for Model Metrology

• URL: http://arxiv.org/abs/2407.16711v1
• Date: Mon, 22 Jul 2024 17:52:12 GMT
• Title: Benchmarks as Microscopes: A Call for Model Metrology
• Authors: Michael Saxon, Ari Holtzman, Peter West, William Yang Wang, Naomi Saphra,
• Abstract summary: Modern language models (LMs) pose a new challenge in capability assessment. To be confident in our metrics, we need a new discipline of model metrology.
• Score: 76.64402390208576
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Modern language models (LMs) pose a new challenge in capability assessment. Static benchmarks inevitably saturate without providing confidence in the deployment tolerances of LM-based systems, but developers nonetheless claim that their models have generalized traits such as reasoning or open-domain language understanding based on these flawed metrics. The science and practice of LMs requires a new approach to benchmarking which measures specific capabilities with dynamic assessments. To be confident in our metrics, we need a new discipline of model metrology -- one which focuses on how to generate benchmarks that predict performance under deployment. Motivated by our evaluation criteria, we outline how building a community of model metrology practitioners -- one focused on building tools and studying how to measure system capabilities -- is the best way to meet these needs to and add clarity to the AI discussion.

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