6 citations · 9 across the 8 of their papers we have counts for
8 papers
Listwise Preference Alignment Optimization for Tail Item Recommendation
Zihao Li, Chao Yang, Tong Zhang +4
Preference alignment has achieved greater success on Large Language Models (LLMs) and drawn broad interest in recommendation research. Existing preference alignment methods for rec…
Enabling Collaborative Parametric Knowledge Calibration for Retrieval-Augmented Vision Question Answering
Jiaqi Deng, Kaize Shi, Zonghan Wu +3
Knowledge-based Vision Question Answering (KB-VQA) systems address complex visual-grounded questions with knowledge retrieved from external knowledge bases. The tasks of knowledge…
Large Language Models are Few-shot Multivariate Time Series Classifiers
Yakun Chen, Zihao Li, Chao Yang +2
Large Language Models (LLMs) have been extensively applied in time series analysis. Yet, their utility in the few-shot classification (i.e., a crucial training scenario due to the…
Graph and Sequential Neural Networks in Session-based Recommendation: A Survey
Zihao Li, Chao Yang, Yakun Chen +5
Recent years have witnessed the remarkable success of recommendation systems (RSs) in alleviating the information overload problem. As a new paradigm of RSs, session-based recommen…
A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation
Yakun Chen, Kaize Shi, Zhangkai Wu +5
Spatiotemporal data analysis is pivotal across various domains, such as transportation, meteorology, and healthcare. The data collected in real-world scenarios are often incomplete…
APLe: Token-Wise Adaptive for Multi-Modal Prompt Learning
Guiming Cao, Kaize Shi, Hong Fu +2
Pre-trained Vision-Language (V-L) models set the benchmark for generalization to downstream tasks among the noteworthy contenders. Many characteristics of the V-L model have been e…
Churn Prediction via Multimodal Fusion Learning:Integrating Customer Financial Literacy, Voice, and Behavioral Data
David Hason Rudd, Huan Huo, Md Rafiqul Islam +1
In todays competitive landscape, businesses grapple with customer retention. Churn prediction models, although beneficial, often lack accuracy due to the reliance on a single data…
GATGPT: A Pre-trained Large Language Model with Graph Attention Network for Spatiotemporal Imputation
Yakun Chen, Xianzhi Wang, Guandong Xu
The analysis of spatiotemporal data is increasingly utilized across diverse domains, including transportation, healthcare, and meteorology. In real-world settings, such data often…