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DBCR - Dual-Branch Compositional Reasoning

Official Repository for:

Chengtai Li, Guosheng Su, Jianfeng Ren, Ruibin Bai, Yitian Zhao, Xudong Jiang. "DBCR: Exploiting Both Intra-cluster and Extra-cluster Relations for Compositional Reasoning". ICASSP 2025.

Overview of DBCR Architecture.

Dataset

  • CVR (NeurIPS 2022)
  • MC2R (IJCAI 2024)

Dependencies

  • numpy: 1.24.4
  • pandas: 1.4.2
  • pillow: 9.0.1
  • python: 3.8.0
  • pytorch-lightning: 1.6.0
  • pyyaml: 6.0.1
  • scikit-learn: 1.0.2
  • scipy: 1.8.0
  • tensorboard: 2.8.0
  • timm: 0.5.4
  • torch: 2.0.1
  • torchvision: 0.15.2

Pretrained Models

The pre-trained ResNet50 can be downloaded from here.

Code

To reproduce the results,

  • In DBCR/jobs/train_array.sh, set checkpoint to path_to_pretrained_model.
  • In DBCR/jobs/train.sh, set data_dir as path_to_dataset, and set WORK_PATH as path_to_experiments.
  • Run the following command
$ ./jobs/train_array.sh

Citation

@inproceedings{li2025dbcr, 
    title={DBCR: Exploiting Both Intra-cluster and Extra-cluster Relations for Compositional Reasoning}, 
    author={Li, Chengtai and Su, Guosheng and Ren, Jianfeng and Bai, Ruibin and Zhao, Yitian and Jiang, Xudong},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
    year={2025}
}

Acknowledgement

We thank the authors of CVR and MC2R for their valuable prior work.

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