11 papers · 1 filter
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…
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…
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…
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…
Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce
Zhiding Liu, Ben Chen, Mingyue Cheng +6
Search-based recommendation is one of the most critical application scenarios in e-commerce platforms. Users' complex search contexts--such as spatiotemporal factors, historical in…
COINS: SemantiC Ids Enhanced COLd Item RepresentatioN for Click-through Rate Prediction in E-commerce Search
Qihang Zhao, Zhongbo Sun, Xiaoyang Zheng +6
With the rise of modern search and recommendation platforms, insufficient collaborative information of cold-start items exacerbates the Matthew effect of existing platform items, c…