11 citations · 25 across the 5 of their papers we have counts for
5 papers
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects
Dong Yao, Caizhi Tang, Qing Cui +1
Data from observational studies (OSs) is widely available and readily obtainable yet frequently contains confounding biases. On the other hand, data derived from randomized control…
Data-Centric Financial Large Language Models
Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou +9
Large language models (LLMs) show promise for natural language tasks but struggle when applied directly to complex domains like finance. LLMs have difficulty reasoning about and in…
Leveraging Large Language Models for Pre-trained Recommender Systems
Zhixuan Chu, Hongyan Hao, Xin Ouyang +9
Recent advancements in recommendation systems have shifted towards more comprehensive and personalized recommendations by utilizing large language models (LLM). However, effectivel…
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift
Yongduo Sui, Qitian Wu, Jiancan Wu +5
The issue of distribution shifts is emerging as a critical concern in graph representation learning. From the perspective of invariant learning and stable learning, a recently well…
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction
Kai Zhang, Hao Qian, Qing Cui +5
In the Click-Through Rate (CTR) prediction scenario, user's sequential behaviors are well utilized to capture the user interest in the recent literature. However, despite being ext…