Frontier Tower AI Paper Reading Club - Week 21 - "Measuring what Matters: Construct Validity in Large Language Model Benchmarks"

​Weekly paper: "Measuring what Matters: Construct Validity in Large Language Model Benchmarks" - https://arxiv.org/abs/2511.04703

Abstract: Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstract and complex phenomena such as 'safety' and 'robustness' requires strong construct validity, that is, having measures that represent what matters to the phenomenon. With a team of 29 expert reviewers, we conduct a systematic review of 445 LLM benchmarks from leading conferences in natural language processing and machine learning. Across the reviewed articles, we find patterns related to the measured phenomena, tasks, and scoring metrics which undermine the validity of the resulting claims. To address these shortcomings, we provide eight key recommendations and detailed actionable guidance to researchers and practitioners in developing LLM benchmarks.

​What are the group goals? Stay on top of AI research, improve understanding of AI fundamentals+math.

​Who is welcome? Everyone! Try to put in at least some time on the paper and come prepared with questions or things you'd like to discuss, but it's ok to just show up.

​How will it work? Ideally everyone shows up and has at least made one solid pass through the paper, and then we can spend 30-60 minutes as a group going over it.

​This event is hosted at the Frontier Tower:

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