Chenxu Wang

E-commerce search relevance modeling faces a critical dilemma: traditional models falter with complex queries, while Large Language Models (LLMs), despite their superior reasoning, suffer from the prohibitive latency of auto-regressive Chain-of-Thought (CoT) generation, rendering them infeasible...

In large-scale e-commerce search, accurately modeling multi-modal relevance is paramount for matching user intent—especially given the growing influence of visual content on shopping decisions. However, existing methods often fail to perform fine-grained reasoning. For instance, they struggle whe...