CFI-Kinds-of-Intelligence/ADeLe_battery_v1dot0

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By accessing this dataset, you accept the conditions to access its files and content. You agree to NOT reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation model training corpora.

Dataset Card for ADeLe

Dataset Summary

ADeLe (Annotated-Demand-Levels) battery is a single, unified test set whose every item is labelled with the level (0-5+) it demands on 18 general ability dimensions (e.g. attention and scan, logical reasoning, various knowledge areas) plus an “unguessability” dimension. It is produced by applying the DeLeAn rubrics, via GPT-4o annotators, to AI benchmarks.

Version 1.0 contains 16 108 items drawn from 63 tasks spread across a diverse collection of 20 AI benchmarks, which are related to broad domains such as math, law, chemistry, temporal reasoning, and more.

Data Leakage

We request that you do not reveal examples from these datasets online in plaintext or image form, for the same reason. If you republish this data, or if you explicitly train models with this data, we request that you share this fact with the authors, such that data contamination can be traced.

Citation Information

If you find our work or the ADeLe battery useful in your research, please consider citing our paper:

@misc{zhou2025generalscalesunlockai,
      title={General Scales Unlock AI Evaluation with Explanatory and Predictive Power}, 
      author={Lexin Zhou and Lorenzo Pacchiardi and Fernando Martínez-Plumed and Katherine M. Collins and Yael Moros-Daval and Seraphina Zhang and Qinlin Zhao and Yitian Huang and Luning Sun and Jonathan E. Prunty and Zongqian Li and Pablo Sánchez-García and Kexin Jiang Chen and Pablo A. M. Casares and Jiyun Zu and John Burden and Behzad Mehrbakhsh and David Stillwell and Manuel Cebrian and Jindong Wang and Peter Henderson and Sherry Tongshuang Wu and Patrick C. Kyllonen and Lucy Cheke and Xing Xie and José Hernández-Orallo},
      year={2025},
      eprint={2503.06378},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2503.06378}, 
}