An unofficial repository of the paper 'A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots' [paper], which is implemented in PyTorch.

The codes have been tested on CMUDoG dataset with 1×V100 GPU, training for 2h.

• Python 3.7
• PyTorch 1.7.0
• fitlog

You can download the datasets and their corresponding embedding tables used in their paper from the following links.

• PERSONA-CHAT and its embedding and vocabulary files.
  
• CMU_DoG and its embedding and vocabulary files.
  

Unzip the datasets to the folder of dataset and run the preprocessing codes provided in JasonForjoy/FIRE.

Then, you will obtain the preprocessing files in dataset/personachat_preprocessed and dataset/cmudog_preprocessed.

Also, we preprocessed the data in advanced, you can also simply run this command to download the preprocessed data:

sh download_dataset.sh

Temporarily we only test on CMUDoG. Here is an example to train DGMN in CMUDoG dataset.

sh run_cmudog.sh

Thank Xueliang Zhao for providing the source codes written in TensorFlow for reference, it does help a lots.

• Evaluate on PersonaChat dataset.
• Check why the reproduced version outperforms the reported result reported in the original paper.