avsolatorio/covid-bing-query-gpt4

---
license: mit
dataset_info:
features:
- name: search
dtype: string
- name: query
dtype: string
- name: pos
dtype: string
splits:
- name: train
num_bytes: 1285026
num_examples: 4973
download_size: 634684
dataset_size: 1285026
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---

# Bing x GPT-4 Synthetic Query Dataset

This dataset was used in the paper GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning. Refer to https://arxiv.org/abs/2402.16829 for details.

The code for generating the data is available at https://github.com/avsolatorio/GISTEmbed.

## Citation
```
@article{solatorio2024gistembed,
title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
author={Aivin V. Solatorio},
journal={arXiv preprint arXiv:2402.16829},
year={2024},
URL={https://arxiv.org/abs/2402.16829}
eprint={2402.16829},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```

原始信息汇总

Bing x GPT-4 Synthetic Query Dataset

数据集信息

特征

• search: 类型为字符串
• query: 类型为字符串
• pos: 类型为字符串

分割

• train:
  • 字节数: 1285026
  • 样本数: 4973

大小

• 下载大小: 634684
• 数据集大小: 1285026

配置

• default:
  • 数据文件:
    • 分割: train
    • 路径: data/train-*

引用

@article{solatorio2024gistembed, title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning}, author={Aivin V. Solatorio}, journal={arXiv preprint arXiv:2402.16829}, year={2024}, URL={https://arxiv.org/abs/2402.16829}, eprint={2402.16829}, archivePrefix={arXiv}, primaryClass={cs.LG} }