MMAPS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization in E-commerce

The source code and datasets for LREC-COLING 2024 paper: MMAPS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization in E-commerce [arXiv preprint].

Folder

• models folder contains the image encoder img_transformer.py, and the overall framework modeling_bart.py.
• utils folder contains the data processing file data_helper.py, and the metric file metric.py.

Environment

The required environment is included in requirements.txt.

Data

The dataset used for experiments is a Chinese E-commerce Product summarization dataset CEPSUM

How to run

To train the model:

python main.py --mode train

To test the model:

python main.py --mode test