16 citations · 17 across the 5 of their papers we have counts for
6 papers
OneLA: Scaling Linear-Attention Decoding to Large Beams in Generative Recommendation
Xiangrui Yang, Cheng Peng, Yunfeng Zhao +9
Generative recommendation (GR) relies on large-beam decoding to generate hundreds of candidate items, creating a new scaling challenge for recurrent linear attention. Existing line…
OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework
Ben Chen, Siyuan Wang, Yufei Ma +20
Generative Retrieval (GR) has emerged as a promising paradigm for modern search systems. Compared to multi-stage cascaded architecture, it offers advantages such as end-to-end join…
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Ben Chen, Xian Guo, Siyuan Wang +25
Traditional e-commerce search systems employ multi-stage cascading architectures (MCA) that progressively filter items through recall, pre-ranking, and ranking stages. While effect…
UniDex: Rethinking Search Inverted Indexing with Unified Semantic Modeling
Zan Li, Jiahui Chen, Yuan Chai +11
Inverted indexing has traditionally been a cornerstone of modern search systems, leveraging exact term matches to determine relevance between queries and documents. However, this t…
UniSearch: Rethinking Search System with a Unified Generative Architecture
Jiahui Chen, Xiaoze Jiang, Zhibo Wang +18
Modern search systems play a crucial role in facilitating information acquisition. Traditional search engines typically rely on a cascaded architecture, where results are retrieved…
One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
Xiang-Rong Sheng, Liqin Zhao, Guorui Zhou +8
Traditional industrial recommenders are usually trained on a single business domain and then serve for this domain. However, in large commercial platforms, it is often the case tha…