14 citations · 34 across the 7 of their papers we have counts for
8 papers
LARA-Gen: Enabling Continuous Emotion Control for Music Generation Models via Latent Affective Representation Alignment
Jiahao Mei, Xuenan Xu, Shimeng Li +7
Recent advances in text-to-music models have enabled coherent music generation from text prompts, yet fine-grained emotional control remains unresolved. We introduce LARA-Gen, a fr…
Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations
Yuhao Yang, Zhi Ji, Zhaopeng Li +8
Generative models have recently gained attention in recommendation systems by directly predicting item identifiers from user interaction sequences. However, existing methods suffer…
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure
Jiyuan Yang, Yue Ding, Yidan Wang +7
Sequential recommendation (SR) models are typically trained on user-item interactions which are affected by the system exposure bias, leading to the user preference learned from th…
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation
Yuxiang Shi, Yue Ding, Bo Chen +4
The cold-start problem is a long-standing challenge in recommender systems due to the lack of user-item interactions, which significantly hurts the recommendation effect over new u…
Extracting Attentive Social Temporal Excitation for Sequential Recommendation
Yunzhe Li, Yue Ding, Bo Chen +5
In collaborative filtering, it is an important way to make full use of social information to improve the recommendation quality, which has been proved to be effective because user…
ICPE: An Item Cluster-Wise Pareto-Efficient Framework for Recommendation Debiasing
Yule Wang, Xin Xin, Yue Ding +2
Recommender system based on historical user-item interactions is of vital importance for web-based services. However, the observed data used to train the recommender model suffers…
DemiNet: Dependency-Aware Multi-Interest Network with Self-Supervised Graph Learning for Click-Through Rate Prediction
Yule Wang, Qiang Luo, Yue Ding +3
In this paper, we propose a novel model named DemiNet (short for DEpendency-Aware Multi-Interest Network) to address the above two issues. To be specific, we first consider various…
Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation
Zhe Xie, Chengxuan Liu, Yichi Zhang +3
Sequential recommendation as an emerging topic has attracted increasing attention due to its important practical significance. Models based on deep learning and attention mechanism…