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---
dataset_info:
features:
- name: query
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
splits:
- name: train
num_bytes: 2766980301
num_examples: 1391986
download_size: 1589194354
dataset_size: 2766980301
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
Training Data For Paper: ["Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?"](https://arxiv.org/abs/2409.02727)
Citation:
```
@misc{poolingattentioneffectivedesigns,
title={Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?},
author={Yixuan Tang and Yi Yang},
year={2024},
eprint={2409.02727},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2409.02727},
}
```
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