VILA🌴
Incorporating VIsual LAyout Structures for Scientific Text Classification

Motivation

Scientific papers typically organize contents in visual groups like text blocks or lines, and text within each group usually have the same semantics. We explore different approaches for injecting the group structure into the text classifiers, and build models that improves the accuracy or efficiency of the scientific text classification task.

Installation

After cloning the github repo, you can either install the vila library or just install the dependencies:

git clone git@github.com:allenai/VILA.git
cd VILA 
conda create -n vila python=3.6
pip install -e . # Install the `vila` library 
pip install -r requirements.txt # Only install the dependencies 

We tested the code and trained the models using Python≥3.6, PyTorch==1.7.1, and transformers==4.4.2.

Usage

Model Inference/Prediction

Training

Citation

@article{Shen2021IncorporatingVL,
  title={Incorporating Visual Layout Structures for Scientific Text Classification},
  author={Zejiang Shen and Kyle Lo and Lucy Lu Wang and Bailey Kuehl and Daniel S. Weld and Doug Downey},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.00676},
  url={https://arxiv.org/abs/2106.00676}
}