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20242026
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cs.IR2026

OneRetrieval: Unifying Multi-Branch E-commerce Retrieval with an Editable Generative Model

Xuxin Zhang, Ben Chen, Yue Lv +13

Industrial e-commerce search serves hundreds of millions of items through a multi-branch retrieval stage fused by hand-tuned merging without joint optimization. Generative retrieva…

cs.IR2026

OneBar: An End-to-End Content-Grounded Generative Query Recommendation Framework for E-Commerce Video Feeds

Yao Tang, Ying Yang, Ben Chen +5

Short-video platforms now expose clickable search entries beneath the video player, enabling users to easily express content-induced search intent. However, conventional query reco…

cs.IR2026

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval

Xinyu Sun, Huangyu Dai, Lingtao Mao +5

E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This image-to-multimodal retrieval se…

cs.IR2026

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…

cs.IR2026

KuaiSearch: An E-Commerce Search Dataset with Authentic Queries and Product Texts for Recall, Ranking, and Relevance

Yupeng Li, Ben Chen, Mingyue Cheng +4

E-commerce search serves as a central interface connecting user demands with massive product inventories and plays a vital role in daily online shopping. However, it faces challeng…

cs.IR2026

Awakening Dormant Users: Generative Recommendation with Counterfactual Functional Role Reasoning

Huishi Luo, Shuokai Li, Hanchen Yang +10

Awakening dormant users, who remain engaged but exhibit low conversion, is a pivotal driver for incremental GMV growth in large-scale e-commerce platforms. However, existing approa…