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Code for the paper "Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews" (ACL 2021)

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MCR: Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews

Code for the paper "Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews" (ACL 2021).

If you use this code, please cite the paper using the BibTeX reference below.

@inproceedings{mcr,
    title={Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews},
    author={Junhao Liu, Zhen Hai, Min Yang, and Lidong Bing},
    booktitle={Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, {ACL} 2021},
    year={2021},
}

Requirements

  • Python >= 3.7
  • PyTorch >= 1.6

You can install all required Python packages with

pip install -r requirements.txt

Datasets

To obtain the multimodal datasets of Lazada-MRHP and Amazon-MRHP, please read the details provided here.

Running the code

Train

Use the following commands to train the model based on the specific configuration file.

# single gpu or data parallel, [ckpt] is optional for continual training
sh scripts/train.sh device_ids config_file [ckpt]

# or distributed training
sh scripts/train_dist.sh device_ids n_procs config_file [ckpt]

Sample configuration files are provided in the config folder.

Evaluate

Do evaluation on a specific dataset based on the saved model checkpoint and corresponding configuration file.

sh scripts/eval.sh device_ids config_file ckpt

Contact

This repo is now under active development, and there may be issues caused by refactoring code. If you have any questions, please feel free to email me at [email protected].

Acknowledgments

Our code is built based on the text matching library MatchZoo and the PyTorch version bottom-up-attention.

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Code for the paper "Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews" (ACL 2021)

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