3 citations · 5 across the 28 of their papers we have counts for
12 papers · 1 filter
UniDGF: A Unified Detection-to-Generation Framework for Hierarchical Object Visual Recognition
Xinyu Nan, Lingtao Mao, Huangyu Dai +8
Achieving visual semantic understanding requires a unified framework that simultaneously handles object detection, category prediction, and attribute recognition. However, current…
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…
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…
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…
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…
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…
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…
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…
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…
UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion
Zihan Liang, Yufei Ma, ZhiPeng Qian +6
Current e-commerce multimodal retrieval systems face two key limitations: they optimize for specific tasks with fixed modality pairings, and lack comprehensive benchmarks for evalu…
OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion
Xian Guo, Ben Chen, Siyuan Wang +4
Query suggestion plays a crucial role in enhancing user experience in e-commerce search systems by providing relevant query recommendations that align with users' initial input. Th…