4 papers
Selective Mixup for Debiasing Question Selection in Computerized Adaptive Testing
Mi Tian, Kun Zhang, Fei Liu +6
Computerized Adaptive Testing (CAT) is a widely used technology for evaluating learners' proficiency in online education platforms. By leveraging prior estimates of proficiency to…
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…
Boosting Explainability through Selective Rationalization in Pre-trained Language Models
Libing Yuan, Shuaibo Hu, Kui Yu +1
The widespread application of pre-trained language models (PLMs) in natural language processing (NLP) has led to increasing concerns about their explainability. Selective rationali…
It is Never Too Late to Mend: Separate Learning for Multimedia Recommendation
Zhuangzhuang He, Zihan Wang, Yonghui Yang +2
Multimedia recommendation, which incorporates various modalities (e.g., images, texts, etc.) into user or item representation to improve recommendation quality, and self-supervised…