Walmart developed a multi-domain language model approach that significantly improves ad retrieval accuracy in their eCommerce platform, addressing unique challenges in sponsored search.

• Implemented a two-tower Siamese Network architecture specialized for matching search queries with relevant product ads
• Developed a progressive knowledge domain training strategy that efficiently adapts language models to different data contexts
• Achieved superior performance compared to traditional methods by effectively handling sparse data and ambiguous search intent
• Successfully deployed in production environment with demonstrated business impact

This engineering innovation demonstrates how tailored language model architectures can solve complex retrieval problems in eCommerce, providing both technical efficiency and business value.

Semantic Ads Retrieval at Walmart eCommerce with Language Models Progressively Trained on Multiple Knowledge Domains