hyounghk / CoSIm

Code and dataset for NAACL 2022 paper "CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination" Hyounghun Kim, Abhay Zala, Mohit Bansal.

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CoSIm

Code and dataset for NAACL 2022 paper "CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination" Hyounghun Kim, Abhay Zala, Mohit Bansal.

Prerequisites

  • Python 3.8
  • PyTorch 1.4 or Up
  • For others packages, please run this command.
pip install -r requirements.txt

Dataset

Please download image features etc. from here and unzip in data/cosim_feats folder.
Raw image files can be downloaded from here.

Usage

To train the models, please run the script run/lxmert_pretrain.bash like below:

bash run/run_train.bash 0  

About

Code and dataset for NAACL 2022 paper "CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination" Hyounghun Kim, Abhay Zala, Mohit Bansal.

License:MIT License


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