5 papers
Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search
Mengxiang Chen, Zhouwei Zhai, Jin Li
Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based paradigms face a fundamental bli…
GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce
Zhouwei Zhai, Min Yang, Jin Li
Faceted search acts as a critical bridge for navigating massive ecommerce catalogs, yet traditional systems rely on static rule-based extraction or statistical ranking, struggling…
SIA: A Synthesize-Inject-Align Framework for Knowledge-Grounded and Secure E-commerce Search LLMs with Industrial Deployment
Zhouwei Zhai, Mengxiang Chen, Anmeng Zhang
Large language models offer transformative potential for e-commerce search by enabling intent-aware recommendations. However, their industrial deployment is hindered by two critica…
CogSearch: A Cognitive-Aligned Multi-Agent Framework for Proactive Decision Support in E-Commerce Search
Zhouwei Zhai, Mengxiang Chen, Haoyun Xia +3
Modern e-commerce search engines, largely rooted in passive retrieval-and-ranking models, frequently fail to support complex decision-making, leaving users overwhelmed by cognitive…
Beyond Retrieval-Ranking: A Multi-Agent Cognitive Decision Framework for E-Commerce Search
Zhouwei Zhai, Mengxiang Chen, Haoyun Xia +3
The retrieval-ranking paradigm has long dominated e-commerce search, but its reliance on query-item matching fundamentally misaligns with multi-stage cognitive decision processes o…