metadata

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 dataset.

Dataset Info

Train: 6,367 examples
Validation: 1,592 examples
Total: 7,959 examples

Usage

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

@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}
}