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PailitaoMMSearch is presented, which directly generates product Semantic IDs from a raw query image and free-form instruction and scales along three dimensions, and is deployed in multimodal search applications on Taobao Pailitao.
Large Language Models (LLMs) have recently shown strong potential for producing context-rich text embeddings for retrieval. Most existing methods either treat embedding learning as passive feature extraction or exploit LLM reasoning through instruction following for better embedding optimization. However, specializatio...
The proposed Prototype-Mediated Process Supervision (PMPS), which introduces learnable reasoning prototypes as semantic anchors to provide structural process-level supervision for latent reasoning, consistently attains the highest accuracy among all latent reasoning methods with comparable output length.
Pailitao-MMSearch is presented, one native e-commerce multimodal search foundation model designed to bridge this gap, and introduces three key innovations:HybSID (Hybrid Semantic ID);(2)a two-stage continual pre-training strategy; and (3)a hybrid reasoning post-training pipeline.
RPS is proposed, a novel training-free decoding method that seeks mid-entropy positions as promising candidate pivots (where to decode), and determines their token assignment that yields the greatest downstream benefit via lookahead evaluation (what to decode).
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