1 citations · 2 across the 12 of their papers we have counts for
6 papers · 1 filter
IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu
Yubin Zhang, Haiming Xu, Guillaume Salha-Galvan +6
Content-driven platforms such as Xiaohongshu often leverage click-through rate (CTR) prediction models for recommendation. However, these models depend heavily on item ID embedding…
LASER: An Efficient Target-Aware Segmented Attention Framework for End-to-End Long Sequence Modeling
Tianhe Lin, Ziwei Xiong, Baoyuan Ou +8
Modeling ultra-long user behavior sequences is pivotal for capturing evolving and lifelong interests in modern recommendation systems. However, deploying such models in real-time i…
QP-OneModel: A Unified Generative LLM for Multi-Task Query Understanding in Xiaohongshu Search
Jianzhao Huang, Xiaorui Huang, Fei Zhao +9
Query Processing (QP) bridges user intent and content supply in large-scale Social Network Service (SNS) search engines. Traditional QP systems rely on pipelines of isolated discri…
HyMiRec: A Hybrid Multi-interest Learning Framework for LLM-based Sequential Recommendation
Jingyi Zhou, Cheng Chen, Kai Zuo +5
Large language models (LLMs) have recently demonstrated strong potential for sequential recommendation. However, current LLM-based approaches face critical limitations in modeling…
Cross-Scenario Unified Modeling of User Interests at Billion Scale
Manjie Xu, Cheng Chen, Xin Jia +9
User interests on content platforms are inherently diverse, manifesting through complex behavioral patterns across heterogeneous scenarios such as search, feed browsing, and conten…
GPRec: Bi-level User Modeling for Deep Recommenders
Yejing Wang, Dong Xu, Xiangyu Zhao +7
GPRec explicitly categorizes users into groups in a learnable manner and aligns them with corresponding group embeddings. We design the dual group embedding space to offer a divers…