Alibaba International E-commerce Product Search Competition DcuRAGONs Team Technical Report
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911239481851904 |
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| author | Nguyen-Ho, Thang-Long Pham, Minh-Khoi Le, Hoang-Bao |
| author_facet | Nguyen-Ho, Thang-Long Pham, Minh-Khoi Le, Hoang-Bao |
| contents | This report details our methodology and results developed for the Multilingual E-commerce Search Competition. The problem aims to recognize relevance between user queries versus product items in a multilingual context and improve recommendation performance on e-commerce platforms. Utilizing Large Language Models (LLMs) and their capabilities in other tasks, our data-centric method achieved the highest score compared to other solutions during the competition. Final leaderboard is publised at https://alibaba-international-cikm2025.github.io. The source code for our project is published at https://github.com/nhtlongcs/e-commerce-product-search. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_25428 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Alibaba International E-commerce Product Search Competition DcuRAGONs Team Technical Report Nguyen-Ho, Thang-Long Pham, Minh-Khoi Le, Hoang-Bao Information Retrieval Artificial Intelligence This report details our methodology and results developed for the Multilingual E-commerce Search Competition. The problem aims to recognize relevance between user queries versus product items in a multilingual context and improve recommendation performance on e-commerce platforms. Utilizing Large Language Models (LLMs) and their capabilities in other tasks, our data-centric method achieved the highest score compared to other solutions during the competition. Final leaderboard is publised at https://alibaba-international-cikm2025.github.io. The source code for our project is published at https://github.com/nhtlongcs/e-commerce-product-search. |
| title | Alibaba International E-commerce Product Search Competition DcuRAGONs Team Technical Report |
| topic | Information Retrieval Artificial Intelligence |
| url | https://arxiv.org/abs/2510.25428 |