RAVEN-FAIR

该数据集名为RAVEN-FAIR，用于评估在训练集和测试集分布相同的环境下答案生成的效果。同时，它也作为一个基准，用以衡量模型在生成智力测试正确答案方面的性能。

This dataset, named RAVEN-FAIR, is intended to evaluate the performance of answer generation in environments where the training and test datasets follow the same distribution. Moreover, it serves as a benchmark for measuring a model's capability to generate correct answers to intelligence tests.

搜集汇总

背景与挑战

背景概述

RAVEN-FAIR是一个平衡的RAVEN数据集，源自CVPR 2021论文'Scale-Localized Abstract Reasoning'，用于抽象推理任务。它通过Python脚本生成，支持创建原始RAVEN或平衡的RAVEN-FAIR版本，需要Python 2.7和特定依赖库。