mlsanityData to 14 Oct 2026

CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets

arXiv 2509.01566 ↗First posted 1 Sep 2025cs.IR cs.CLcited by 1

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Abstract (arXiv)

As global e-commerce platforms continue to expand, companies are entering new markets where they encounter cold-start challenges due to limited human labels and user behaviors. In this paper, we share our experiences in Coupang to provide a competitive cold-start performance of relevance matching for emerging e-commerce markets. Specifically, we present a Cold-Start Relevance Matching (CSRM) framework, utilizing a multilingual Large Language Model (LLM) to address three challenges: (1) activating cross-lingual transfer learning abilities of LLMs through machine translation tasks; (2) enhancing query understanding and incorporating e-commerce knowledge by retrieval-based query augmentation; (3) mitigating the impact of training label errors through a multi-round self-distillation training strategy. Our experiments demonstrate the effectiveness of CSRM-LLM and the proposed techniques, resulting in successful real-world deployment and significant online gains, with a 45.8% reduction in defect ratio and a 0.866% uplift in session purchase rate.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 24 references that are in the map. First posted on arXiv 1 Sep 2025.

Builds on

12 of 24 references.

References · 12

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025Alibaba International E-commerce Product Search Competition DILAB Team Technical Reportcited by 0

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  3. 2025LREF: A Novel LLM-based Relevance Framework for E-commerce
  4. 2025A Technical Report on the Second Place Solution for the CIKM 2025 AnalytiCup Competition ↗
  5. 2024Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models
  6. 2025Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia
  7. 2025Knowledge Distillation for Enhancing Walmart E-commerce Search Relevance Using Large Language Models
  8. 2025Aligning LLMs for Multilingual Consistency in Enterprise Applications