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.
翻译：本报告详细阐述了我们在多语言电商搜索竞赛中开发的方法与成果。该问题旨在识别多语言环境下用户查询与产品条目之间的相关性，并提升电商平台上的推荐性能。通过利用大语言模型（LLMs）及其在其他任务中的能力，我们以数据为中心的方法在竞赛中取得了相较于其他解决方案的最高分数。最终排行榜发布于 https://alibaba-international-cikm2025.github.io。本项目的源代码发布于 https://github.com/nhtlongcs/e-commerce-product-search。
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