Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results
AI evaluations are widely used for testing and understanding progress. However, the diverse evaluators bring with them inconsistencies that challenge analysis and comparison. First, results are saved in incompatible formats, scattered across leaderboards, papers, blog posts, evaluation harness logs, and custom repositories. Second, results are created by different evaluation frameworks, which produce divergent scores for nominally identical evaluations and record metadata inconsistently, hindering comparison, cross-community evaluation science, cost reduction, and reuse. We introduce Every Eval Ever, the first shared schema and community-crowdsourced repository for AI evaluation results. ...
| Authors | Jan Batzner, Sree Harsha Nelaturu, Damian Stachura et al. |
|---|---|
| Primary category | cs.AI |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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- evaleval/EEE_datastoreDataset
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