---
license: apache-2.0
task_categories:
- text-generation
language:
- zh
pretty_name: MD2T
size_categories:
- 100K<n<1M
---
MD2T is a new setting for multimodal E-commerce Description generation based on structured keywords and images.

Our paper (LREC-COLING 2024): [A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation](https://arxiv.org/abs/2402.13587).

# MD2T Dataset Statistics

| MD2T      | Cases&Bags | Clothing | Home Appliances |
|-----------|------------|----------|-----------------|
| #Train    | 18,711     | 200,000  | 86,858          |
| #Dev      | 983        | 6,120    | 1,794           |
| #Test     | 1,000      | 8,700    | 2,200           |
| Avg_N #MP | 5.41       | 6.57     | 5.48            |
| Avg_L #MP | 13.50      | 20.34    | 18.30           |
| Avg_L #Desp | 80.05    | 79.03    | 80.13           |

**Table 1:** The detailed statistics of MD2T. Avg_N and Avg_L represent the average number and length respectively. MP and Desp indicate the marketing keywords and description.


# Cite our Work

```
@article{li2024multimodal,
  title={A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation},
  author={Li, Yunxin and Hu, Baotian and Luo, Wenhan and Ma, Lin and Ding, Yuxin and Zhang, Min},
  journal={arXiv preprint arXiv:2402.13587},
  year={2024}
}
```