Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchandise value (GMV) per user. However, such objectives are defined at the user level, whereas search ranking is based on item-level scores within each request. Existing met...
Jun-Zhao Zhang, Tao Zhang, Liron Yu et al.· 0 citations
TSSR-Beta (Taobao Search Semantic Retrieval Model - Beta), which improves the expressiveness of the production Dual-Encoder TSSR through a plug-in similarity module, termed the Hybrid Interaction Head, which introduces fine-grained matching in the representation space through two complementary pathways.
Guo-Hao Tan, Jia-Hui Wan, Tao Wen et al.· Proceedings of the 20th ACM...· 0 citations
This work introduces EAVer, an End-to-end Agentic Verifier that learns to control the complete response-level verification workflow as a unified policy, and construct 794 bidirectional same-trajectory preference pairs that keep claim grouping, search, and evidence fixed, enabling decision-focused Direct Preference Opti...
Ke-Ning Zheng, Ao-Ying Zheng, Zhi-Gang Chang et al.· 0 citations
This work proposes the Cluster-Ranked Identifier (CRID), which decouples DocID into semantic clustering and business-value ranking, yielding collision-free identifiers that support incremental updates via intra-cluster reranking.
Gui Ling, Zhihong Chen, Yu Li et al.· arXiv.org· 2 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
Generative retrieval has become an increasingly adopted paradigm for industrial search, recommendation, and advertising systems, delivering significant online gains. Most existing work combines user behavior sequences with large language models (LLMs) to model user preferences. In practice, feature engineering remains...
Dan Ou, Gui Ling, Haokai Wan et al.· 0 citations
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