---
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}, 
}

```