collaborators

11 papers

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.AI2026

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…

cs.AI2026

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…

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.AI2026

SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning

Yufei Ma, Zihan Liang, Ben Chen +6

Search-augmented reasoning agents interleave internal reasoning with calls to an external retriever, and their performance relies on the quality of each issued query. However, unde…

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…