167 citations · 397 across the 33 of their papers we have counts for
7 papers · 1 filter
TopoGR: Revealing and Preserving Latent Structure of Semantic ID in Generative Recommendation
Ziyu Zheng, Zhengshun Du, Yaming Yang +5
Semantic ID-based generative recommendation tokenizes each item into a sequence of discrete semantic IDs and predicts the next item by generating semantic IDs. However, existing me…
EviRank: Evidence-Based Confidence Estimation for LLM-Based Ranking
Meng Yan, Cai Xv, Xujing Wang +2
Large Language Models show promise for recommendation, but they raise reliability concerns due to limited domain coverage and inherent stochasticity. Existing uncertainty quantific…
Differentiable Geometric Indexing for End-to-End Generative Retrieval
Xujing Wang, Yufeng Chen, Boxuan Zhang +7
Generative Retrieval (GR) has emerged as a promising paradigm to unify indexing and search within a single probabilistic framework. However, existing approaches suffer from two int…
Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing
Zhe Wang, Yaming Yang, Ziyu Guan +4
In recent years, affiliate marketing has emerged as a revenue-sharing strategy where merchants collaborate with promoters to promote their products. It not only increases product e…
TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal Content
Meng Yan, Haibin Huang, Ying Liu +5
Sequential recommender systems explore users' preferences and behavioral patterns from their historically generated data. Recently, researchers aim to improve sequential recommenda…
IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
Jun Zhao, Zhou Zhou, Ziyu Guan +4
The remarkable progress of network embedding has led to state-of-the-art algorithms in recommendation. However, the sparsity of user-item interactions (i.e., explicit preferences)…
Personalized Attraction Enhanced Sponsored Search with Multi-task Learning
Wei Zhao, Boxuan Zhang, Beidou Wang +6
We study a novel problem of sponsored search (SS) for E-Commerce platforms: how we can attract query users to click product advertisements (ads) by presenting them features of prod…