Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
json
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
100K - 1M
ArXiv:
License:
| license: mit | |
| language: | |
| - en | |
| paperswithcode_id: embedding-data/SPECTER | |
| pretty_name: SPECTER | |
| # Dataset Card for "ESPECTER" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [https://github.com/allenai/specter](https://github.com/allenai/specter) | |
| - **Repository:** [More Information Needed](https://github.com/allenai/specter/blob/master/README.md) | |
| - **Paper:** [More Information Needed](https://arxiv.org/pdf/2004.07180.pdf) | |
| - **Point of Contact:** [@armancohan](https://github.com/armancohan), [@sergeyf](https://github.com/sergeyf), [@haroldrubio](https://github.com/haroldrubio), [@jinamshah](https://github.com/jinamshah) | |
| - **Size of downloaded dataset files:** | |
| - **Size of the generated dataset:** | |
| - **Total amount of disk used:** 38.3 MB | |
| ### Dataset Summary | |
| SPECTER: Document-level Representation Learning using Citation-informed Transformers. | |
| A new method to generate document-level embedding of scientific documents based on | |
| pretraining a Transformer language model on a powerful signal of document-level relatedness: the citation graph. | |
| Unlike existing pretrained language models, SPECTER can be easily applied to | |
| downstream applications without task-specific fine-tuning. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Languages | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ## Dataset Structure | |
| Specter requires two main files as input to embed the document. | |
| A text file with ids of the documents you want to embed and a json metadata file | |
| consisting of the title and abstract information. | |
| Sample files are provided in the `data/` directory to get you started. | |
| Input data format is according to: | |
| metadata.json format: | |
| ``` | |
| { | |
| 'doc_id': {'title': 'representation learning of scientific documents', | |
| 'abstract': 'we propose a new model for representing abstracts'}, | |
| } | |
| ``` | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/allenai/specter) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/allenai/specter) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Licensing Information | |
| [More Information Needed](https://github.com/allenai/specter) | |
| ### Citation Information | |
| ``` | |
| @inproceedings{specter2020cohan, | |
| title={{SPECTER: Document-level Representation Learning using Citation-informed Transformers}}, | |
| author={Arman Cohan and Sergey Feldman and Iz Beltagy and Doug Downey and Daniel S. Weld}, | |
| booktitle={ACL}, | |
| year={2020} | |
| } | |
| ``` | |
| SciDocs benchmark | |
| SciDocs evaluation framework consists of a suite of evaluation tasks designed for document-level tasks. | |
| Link to SciDocs: | |
| - [https://github.com/allenai/scidocs](https://github.com/allenai/scidocs) | |
| ### Contributions | |
| Thanks to [@armancohan](https://github.com/armancohan), [@sergeyf](https://github.com/sergeyf), [@haroldrubio](https://github.com/haroldrubio), [@jinamshah](https://github.com/jinamshah) | |