Knowledge tracing, which estimates students' knowledge states by predicting the probability
that they correctly answer questions, is an essential task for online learning platforms. It has …

Building a multi-stage cascade ranking system is a commonly used solution to balance the
efficiency and effectiveness in modern information retrieval (IR) applications, such as …

With large language models (LLMs) achieving remarkable breakthroughs in NLP domains,
LLM-enhanced recommender systems have received much attention and have been …

Prediction over tabular data is an essential and fundamental problem in many important
downstream tasks. However, existing methods either take a data instance of the table …

Data science is concerned with mining data patterns from a database, which is assembled
by tabular data. As the routine of machine learning, most of the previous work mining the …

Click-through rate (CTR) estimation plays a crucial role in modern online personalization
services. It is essential to capture users' drifting interests by modeling sequential user …

Due to the comprehensive influencing factors, accurate fatigue life prediction of materials is
still a challenging task. In the present study, a novel deep learning approach named Multi …

As one of the fundamental trends for future development of recommender systems, Fashion
Clothes Matching Recommendation for click-through rate (CTR) prediction has become an …

Prediction over tabular data is often a crucial task in many real-life applications. Recent
advances in deep learning give rise to various deep models for tabular data prediction. A …

In line with the increasing machine learning model inference accuracy, deep learning (DL)
models have been increasingly applied to structured data for a wide spectrum of real-world …