2025 EMNLP EMNLP 2025

Cost-Effective E-Commerce Catalog Translation at Scale Ensuring Named Entity Protection

Abstract

AbstractWe present an enterprise-grade translation platform for global e-commerce that combines daily batch and real-time API pipelines with optimized T5-based models and a Reference Generator to enforce >99% non-translatable entity preservation. A linguist-driven rule engine and explainable evaluation framework (BLEU, COMET, and a custom e-commerce metric) enable continuous quality improvements. Deployed on GPU-accelerated inference servers and CPU-based processing nodes, our system processes millions of listings per day with sub-second latency and achieves 10×–100× cost savings over general-purpose LLMs for English→Spanish and English→French translation, all while version-tracking every update for robust enterprise rollouts.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio