most citedExplicit Time Embedding Based Cascade Attention Network for Information Popularity Prediction

32 citations · 49 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20241 cited

FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Ziqiang Yuan, Kaiyuan Wang, Shoutai Zhu +4

Large Language models (LLMs) usually rely on extensive training datasets. In the financial domain, creating numerical reasoning datasets that include a mix of tables and long text…

cs.SI20235 cited

DySuse: Susceptibility Estimation in Dynamic Social Networks

Yingdan Shi, Jingya Zhou, Congcong Zhang

Influence estimation aims to predict the total influence spread in social networks and has received surged attention in recent years. Most current studies focus on estimating the t…

cs.SI202311 cited

Fairness-aware Competitive Bidding Influence Maximization in Social Networks

Congcong Zhang, Jingya Zhou, Jin Wang +2

Competitive Influence Maximization (CIM) has been studied for years due to its wide application in many domains. Most current studies primarily focus on the micro-level optimizatio…

cs.SI202332 cited

Explicit Time Embedding Based Cascade Attention Network for Information Popularity Prediction

Xigang Sun, Jingya Zhou, Ling Liu +1

Predicting information cascade popularity is a fundamental problem in social networks. Capturing temporal attributes and cascade role information (e.g., cascade graphs and cascade…

cs.LG2023

Securing Distributed SGD against Gradient Leakage Threats

Wenqi Wei, Ling Liu, Jingya Zhou +2

This paper presents a holistic approach to gradient leakage resilient distributed Stochastic Gradient Descent (SGD). First, we analyze two types of strategies for privacy-enhanced…