Embedding-based retrieval (EBR) is pivotal in e-commerce search but often struggles with complex semantics. While recent methods often fine-tune large language models (LLMs) for representation learning, they typically lack robust mechanisms for handling complex and implicit semantics. While Retrieval-GRPO (R-GRPO) rece...
Guangxin Song, Xingye Fang, Ming-Min Jin et al.· 0 citations
Integrating recall and pre-ranking in e-commerce search requires candidate generation to account for relevance, personalization, and business value before final ranking. To this end, we present VARG, a generative retrieval system for Tmall App search that directly admits generated item candidates to the existing final...
Xiao-Peng Chu, Jian-Bo Zhu, Ming-Min Jin et al.· 0 citations
In large-scale industrial search and ranking systems, Click-Through Rate (CTR) prediction is undergoing a paradigm shift from traditional Deep Learning Recommendation Models (DLRM) toward unified, compute-intensive Transformer architectures. The primary motivation for this transition is to leverage Model FLOPs Utilizat...
Zhentao Song, Yufeng Gao, Xingye Fang et al.· Proceedings of the 32nd ACM...· 0 citations
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