cx-cmu/GEO-Bench

这是一个名为GEO-Bench Dataset (AutoGEO)的研究领域数据集，主要用于生成引擎优化(GEO)研究。数据集包含多个配置：main（用于GEO训练和评估的主要训练/测试数据，约8k训练/1k测试样本）、rule_candidate（用于内容偏好规则提取的数据，约8k样本）、cold_start（用于AutoGEO Mini的监督微调数据，约3.5k样本）、inference（仅用于推理的数据，约1k样本）、grpo_input（用于GRPO训练的输入数据，约8k样本）和grpo_eval（用于GRPO训练模型的评估数据，约8k样本）。数据集与论文《What Generative Search Engines Like and How to Optimize Web Content Cooperatively》相关联，并提供了GitHub代码链接和引用信息。

This is a research-domain dataset named GEO-Bench Dataset (AutoGEO) released for Generative Engine Optimization (GEO) research. The dataset includes multiple configurations: main (primary train/test data for GEO training and evaluation, ~8k train / ~1k test samples), rule_candidate (data for content preference rule extraction, ~8k samples), cold_start (supervised fine-tuning data for AutoGEO Mini, ~3.5k samples), inference (inference-only data, ~1k samples), grpo_input (input data for GRPO training, ~8k samples), and grpo_eval (evaluation data for GRPO-trained models, ~8k samples). The dataset is associated with the paper What Generative Search Engines Like and How to Optimize Web Content Cooperatively and provides GitHub code links and citation information.