Developing and Maintaining an Open-Source Repository of AI Evaluations: Challenges and Insights

Alexandra Abbas, Celia Waggoner, Justin Olive
7/9/2025
cs.CLcs.AI

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

AI evaluations have become critical tools for assessing large language model capabilities and safety. This paper presents practical insights from eight months of maintaining $inspect\_evals$, an open-source repository of 70+ community-contributed AI evaluations. We identify key challenges in implementing and maintaining AI evaluations and develop solutions including: (1) a structured cohort management framework for scaling community contributions, (2) statistical methodologies for optimal resampling and cross-model comparison with uncertainty quantification, and (3) systematic quality control processes for reproducibility. Our analysis reveals that AI evaluation requires specialized infrastructure, statistical rigor, and community coordination beyond traditional software development practices.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence

85% match2024

Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

84% match2024

Towards More Standardized AI Evaluation: From Models to Agents

83% match2026

Data and AI governance: Promoting equity, ethics, and fairness in large language models

83% match1 repo2025

Large Language Models Often Know When They Are Being Evaluated

83% match2025

Is Open Source the Future of AI? A Data-Driven Approach

83% match2025

Cite this paper

@article{abbas2025developing,
  title  = {Developing and Maintaining an Open-Source Repository of AI Evaluations: Challenges and Insights},
  author = {Alexandra Abbas and Celia Waggoner and Justin Olive},
  year   = {2025},
  eprint = {2507.06893},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.06893v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2507.06893.svg)](https://codeofpaper.com/paper/2507.06893)

Discussion