most citedUniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion

1 citations · 2 across the 6 of their papers we have counts for

collaborators

8 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.LG2025

GRADE: Personalized Multi-Task Fusion via Group-relative Reinforcement Learning with Adaptive Dirichlet Exploration

Tingfeng Hong, Pingye Ren, Xinlong Xiao +4

Balancing multiple objectives is critical for user satisfaction in modern recommender and search systems, yet current Multi-Task Fusion (MTF) methods rely on static, manually-tuned…

cs.CV2025

OneVision: An End-to-End Generative Framework for Multi-view E-commerce Vision Search

Zexin Zheng, Huangyu Dai, Lingtao Mao +8

Traditional vision search, similar to search and recommendation systems, follows the multi-stage cascading architecture (MCA) paradigm to balance efficiency and conversion. Specifi…

cs.IR2025

InfoGain-RAG: Boosting Retrieval-Augmented Generation via Document Information Gain-based Reranking and Filtering

Zihan Wang, Zihan Liang, Zhou Shao +7

Retrieval-Augmented Generation (RAG) has emerged as a promising approach to address key limitations of Large Language Models (LLMs), such as hallucination, outdated knowledge, and…

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…

cs.SD2025

H-PRM: A Pluggable Hotword Pre-Retrieval Module for Various Speech Recognition Systems

Huangyu Dai, Lingtao Mao, Ben Chen +5

Hotword customization is crucial in ASR to enhance the accuracy of domain-specific terms. It has been primarily driven by the advancements in traditional models and Audio large lan…