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---
license: cc-by-4.0
task_categories:
- text-classification
- information-retrieval
tags:
- reranking
- scientific-papers
- MTEB
language:
- en
size_categories:
- 1K<n<10K
---
# SciDocs Reranking with Train Split
This dataset adds a training split to the original [mteb/scidocs-reranking](https://huggingface.co/datasets/mteb/scidocs-reranking) dataset.
## Dataset Info
- **Train**: 6,367 examples
- **Validation**: 1,592 examples
- **Total**: 7,959 examples
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("Bibek/scidocs-reranking-train")
train_data = dataset['train']
val_data = dataset['validation']
```
## Original Dataset
Based on the SciDocs benchmark from the SPECTER paper:
- Paper: https://arxiv.org/abs/2004.07180
- Original: https://huggingface.co/datasets/mteb/scidocs-reranking
## Citation
```bibtex
@inproceedings{cohan2020specter,
title={SPECTER: Document-level Representation Learning using Citation-informed Transformers},
author={Arman Cohan and Sergey Feldman and Iz Beltagy and Doug Downey and Daniel Weld},
booktitle={ACL},
year={2020}
}
```
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