6 papers
Requirement--Evidence Alignment for Compositional E-Commerce Queries
Weihao Shen, Wei Chen, Fuwei Zhang +6
Compositional e-commerce queries express multiple requirements that must hold jointly, yet existing rerankers collapse these constraints into aggregate relevance and often promote…
Unpaired Modality-Agnostic Generative Recommendation
Weihao Shen, Wei Chen, Fuwei Zhang +6
Generative Recommendation (GR) formulates recommendation as autoregressive generation over discrete semantic identifiers (IDs). Although recent multimodal GR methods improve semant…
CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search
Zhi Jin, Xi Wang, Yunfei Li +3
Ranking relevance is a fundamental task in e-commerce search, directly affecting ranking quality and consumer experience. Although inherently an ordinal classification problem, it…
CAT-ID: Category-Tree Integrated Document Identifier Learning for Generative Retrieval In E-commerce
Xiaoyu Liu, Fuwei Zhang, Yiqing Wu +6
Generative retrieval (GR) has gained significant attention as an effective paradigm that integrates the capabilities of large language models (LLMs). It generally consists of two s…
A Soft-partitioned Semi-supervised Collaborative Transfer Learning Approach for Multi-Domain Recommendation
Xiaoyu Liu, Yiqing Wu, Ruidong Han +3
In industrial practice, Multi-domain Recommendation (MDR) plays a crucial role. Shared-specific architectures are widely used in industrial solutions to capture shared and unique a…
IterQR: An Iterative Framework for LLM-based Query Rewrite in e-Commercial Search System
Shangyu Chen, Xinyu Jia, Yingfei Zhang +3
The essence of modern e-Commercial search system lies in matching user's intent and available candidates depending on user's query, providing personalized and precise service. Howe…