This work introduces SHOPPER, which addresses bottlenecks in large-scale e-commerce recommendation systems through Semantic history, order-aware local intent modeling, and serving-aware factorization, enabling deep target-aware summarization.
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.· 1 citation
This work proposes EAGER (Enrich-and-AliGn gEnerative Query Recommendation), a two-stage framework for generating query suggestions from clicked items that has been deployed in production at a major e-commerce platform.
Shu-Wei Yuan, Mingyu Ding, Lu-Xin Liu et al.· 0 citations
The results show that a shared semantic product hierarchy can support both recommendation and search while preserving the task-specific context required by each application.
Steven Xu, Sanjyot Thete, Saathvik Dirisala et al.· 0 citations
Traditional e-commerce search platforms rely heavily on inverted indices and token-level lexical matching algorithms (e.g., BM25 and TF-IDF), which frequently fail on conversational, intent-driven, or paraphrased user queries -- the classic vocabulary mismatch problem. We formulate conversational product recommendation...
CAIRO, a user context-aware item profiling framework for LLM-based reranking, first structures raw metadata and reviews into objective features and subjective traits, and employs a lightweight profiler to select the most relevant information for each user-item pair with limited serving-time overhead.
Dojun Hwang, Seunghan Lee, Cheonyoung Park et al.· 0 citations
This work introduces a two-level framework that distills LLM reasoning into an efficient non-generative student and adapts its decision boundary to product-type-specific trade-up criteria.
Si-Liang Liu, Mohammadhasan Ghasemi, Sapan Patel et al.· 0 citations
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