Zhenhua Dong

Dual Sequence Transformer for Query-based Interactive Recommendation

2021

Interactive recommendation has drawn widespread attention from both academia and industry due to its effectiveness in real-world mobile applications. Instead of receiving message passively, customers can exploit further with less effort through generated queries. Usually, …

A Brief History of Recommender Systems

2022 · arXiv (Cornell University)

Soon after the invention of the Internet, the recommender system emerged and related technologies have been extensively studied and applied by both academia and industry. Currently, recommender system has become one of the most successful …

Beyond Single-Point Judgment: Distribution Alignment for LLM-as-a-Judge

2025 · arXiv (Cornell University)

LLMs have emerged as powerful evaluators in the LLM-as-a-Judge paradigm, offering significant efficiency and flexibility compared to human judgments. However, previous methods primarily rely on single-point evaluations, overlooking the inherent diversity and uncertainty in human …

Noninvasive Self-attention for Side Information Fusion in Sequential Recommendation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Sequential recommender systems aim to model users’ evolving interests from their historical behaviors, and hence make customized time-relevant recommendations. Compared with traditional models, deep learning approaches such as CNN and RNN have achieved remarkable advancements …

SimpleX

2021

Collaborative filtering (CF) is a widely studied research topic in recommender systems. The learning of a CF model generally depends on three major components, namely interaction encoder, loss function, and negative sampling. While many existing …