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...
Zi-Han Gong, Xiaohan Ye, Jiang-Chao Yao et al.· 0 citations
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.
Xiaohan Ye, Xu Chen, Zi-Han Gong et al.· arXiv.org· 0 citations
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).
Yu-Shi Ye, Xu Chen, Hao-Yun Jiang et al.· 1 citation
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