readme: ---
  language:
  - sci
  - en
  tags:
  - classification
  - similarity
  license: mit
  datasets:
  - acl-arc
  ---
  
  # Aspect-based Document Similarity for Research Papers
  
  A `scibert-scivocab-uncased` model fine-tuned on the ACL Anthology corpus as in [Aspect-based Document Similarity for Research Papers](https://arxiv.org/abs/2010.06395).
  
  <img src="https://raw.githubusercontent.com/malteos/aspect-document-similarity/master/docrel.png">
  
  See GitHub for more details: https://github.com/malteos/aspect-document-similarity
  
  ## Demo
  
  <a href="https://colab.research.google.com/github/malteos/aspect-document-similarity/blob/master/demo.ipynb"><img src="https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Google Colab"></a>
  
  You can try our trained models directly on Google Colab on all papers available on Semantic Scholar (via DOI, ArXiv ID, ACL ID, PubMed ID):
  
  <a href="https://colab.research.google.com/github/malteos/aspect-document-similarity/blob/master/demo.ipynb"><img src="https://raw.githubusercontent.com/malteos/aspect-document-similarity/master/demo.gif" alt="Click here for demo"></a>
  
  