activity
20202025
most citedUtilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach

1 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.IR20251 cited

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…

cs.IR2025

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…

cs.IR2025

Adaptive User Interest Modeling via Conditioned Denoising Diffusion For Click-Through Rate Prediction

Qihang Zhao, Xiaoyang Zheng, Ben Chen +2

User behavior sequences in search systems resemble "interest fossils", capturing genuine intent yet eroded by exposure bias, category drift, and contextual noise. Current methods p…

cs.IR2025

DiffusionGS: Generative Search with Query Conditioned Diffusion in Kuaishou

Qinyao Li, Xiaoyang Zheng, Qihang Zhao +6

Personalized search ranking systems are critical for driving engagement and revenue in modern e-commerce and short-video platforms. While existing methods excel at estimating users…

q-bio.GN20241 cited

dnaGrinder: a lightweight and high-capacity genomic foundation model

Qihang Zhao, Chi Zhang, Weixiong Zhang

The task of understanding and interpreting the complex information encoded within genomic sequences remains a grand challenge in biological research and clinical applications. In t…

cs.IR2024

Redefining Information Retrieval of Structured Database via Large Language Models

Mingzhu Wang, Yuzhe Zhang, Qihang Zhao +2

Retrieval augmentation is critical when Language Models (LMs) exploit non-parametric knowledge related to the query through external knowledge bases before reasoning. The retrieved…