How Meituan Search 3.0 Leverages LLM Semantic Representations to Boost Ranking
The article details Meituan Search 3.0’s three‑phase journey—validating LLM‑based semantic vectors, rebuilding a systematic representation pipeline with contrastive learning and LoRA, and transferring the model to downstream item ranking—showing how 64‑dimensional cosine similarity features and multi‑scale embeddings consistently improve click, order and NDCG metrics across service‑retail search scenarios.
