4 papers
PureCC: Pure Learning for Text-to-Image Concept Customization
Zhichao Liao, Xiaole Xian, Qingyu Li +7
Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often neglect the influence on the original…
Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
Miaomiao Cai, Min Hou, Lei Chen +4
Collaborative Filtering~(CF) plays a crucial role in modern recommender systems, leveraging historical user-item interactions to provide personalized suggestions. However, CF-based…
Disentangled Interest Network for Out-of-Distribution CTR Prediction
Yu Zheng, Chen Gao, Jianxin Chang +5
Click-through rate (CTR) prediction, which estimates the probability of a user clicking on a given item, is a critical task for online information services. Existing approaches oft…
Distilling Textual Priors from LLM to Efficient Image Fusion
Ran Zhang, Xuanhua He, Ke Cao +4
Multi-modality image fusion aims to synthesize a single, comprehensive image from multiple source inputs. Traditional approaches, such as CNNs and GANs, offer efficiency but strugg…