16 citations · 38 across the 12 of their papers we have counts for
12 papers
FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis
Ziao Wang, Yuhang Li, Junda Wu +2
In this paper, we propose FinVis-GPT, a novel multimodal large language model (LLM) specifically designed for financial chart analysis. By leveraging the power of LLMs and incorpor…
GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs
Linhao Luo, Yixiang Fang, Moli Lu +3
Heterogeneous graphs, which contain nodes and edges of multiple types, are prevalent in various domains, including bibliographic networks, social media, and knowledge graphs. As a…
VDPC: Variational Density Peak Clustering Algorithm
Yizhang Wang, Di Wang, You Zhou +2
The widely applied density peak clustering (DPC) algorithm makes an intuitive cluster formation assumption that cluster centers are often surrounded by data points with lower local…
Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
Linhao Luo, Yixiang Fang, Xin Cao +2
Community detection, aiming to group the graph nodes into clusters with dense inner-connection, is a fundamental graph mining task. Recently, it has been studied on the heterogeneo…
DAGNN: Demand-aware Graph Neural Networks for Session-based Recommendation
Liqi Yang, Linhan Luo, Lifeng Xin +2
Session-based recommendations have been widely adopted for various online video and E-commerce Websites. Most existing approaches are intuitively proposed to discover underlying in…
Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning
Shiyi Chen, Ziao Wang, Xinni Zhang +2
Graph representation learning has long been an important yet challenging task for various real-world applications. However, their downstream tasks are mainly performed in the setti…
RRCN: A Reinforced Random Convolutional Network based Reciprocal Recommendation Approach for Online Dating
Linhao Luo, Liqi Yang, Ju Xin +6
Recently, the reciprocal recommendation, especially for online dating applications, has attracted more and more research attention. Different from conventional recommendation probl…
Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation
Yunpeng Ren, Ziao Wang, Yiyuan Wang +1
Automatically generating financial report from a piece of news is quite a challenging task. Apparently, the difficulty of this task lies in the lack of sufficient background knowle…
Automatically Generating Macro Research Reports from a Piece of News
Wenxin Hu, Xiaofeng Zhang, Gang Yang
Automatically generating macro research reports from economic news is an important yet challenging task. As we all know, it requires the macro analysts to write such reports within…
Structure Matters: Towards Generating Transferable Adversarial Images
Dan Peng, Zizhan Zheng, Linhao Luo +1
Recent works on adversarial examples for image classification focus on directly modifying pixels with minor perturbations. The small perturbation requirement is imposed to ensure t…
Wasserstein Autoencoders for Collaborative Filtering
Jingbin Zhong, Xiaofeng Zhang
The recommender systems have long been investigated in the literature. Recently, users' implicit feedback like `click' or `browse' are considered to be able to enhance the recommen…
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Dan Peng, Zizhan Zheng, Xiaofeng Zhang
Adversarial examples are perturbed inputs designed to fool machine learning models. Most recent works on adversarial examples for image classification focus on directly modifying p…