21 papers
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…
Plan Before Search: Search Agents Need Plan
Zhipeng Qian, Zihan Liang, Yufei Ma +7
Training large language models as retrieval-augmented reasoning agents typically combines reinforcement learning with an SFT cold start distilled from a stronger model. However, th…
Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning
Zihan Liang, Yufei Ma, Ben Chen +4
Post-training has become the dominant recipe for turning a language model into a competent search-augmented reasoning agent. A line of recent work pushes its performance further by…
SVFSearch: A Multimodal Knowledge-Intensive Benchmark for Short-Video Frame Search in the Gaming Vertical Domain
Lingtao Mao, Huangyu Dai, Xinyu Sun +4
Multimodal large language models are increasingly used as agent backbones that understand multimodal inputs, plan retrieval actions, invoke external tools, and reason over retrieve…
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…