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--- |
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license: apache-2.0 |
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task_categories: |
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- text-generation |
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language: |
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- zh |
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pretty_name: MD2T |
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size_categories: |
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- 100K<n<1M |
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--- |
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MD2T is a new setting for multimodal E-commerce Description generation based on structured keywords and images. |
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Our paper (LREC-COLING 2024): [A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation](https://arxiv.org/abs/2402.13587). |
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# MD2T Dataset Statistics |
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|
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| MD2T | Cases&Bags | Clothing | Home Appliances | |
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|-----------|------------|----------|-----------------| |
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| #Train | 18,711 | 200,000 | 86,858 | |
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| #Dev | 983 | 6,120 | 1,794 | |
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| #Test | 1,000 | 8,700 | 2,200 | |
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| Avg_N #MP | 5.41 | 6.57 | 5.48 | |
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| Avg_L #MP | 13.50 | 20.34 | 18.30 | |
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| Avg_L #Desp | 80.05 | 79.03 | 80.13 | |
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**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. |
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# Cite our Work |
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``` |
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@article{li2024multimodal, |
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title={A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation}, |
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author={Li, Yunxin and Hu, Baotian and Luo, Wenhan and Ma, Lin and Ding, Yuxin and Zhang, Min}, |
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journal={arXiv preprint arXiv:2402.13587}, |
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year={2024} |
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} |
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``` |
