Hanghang Tong

Task-Adversarial Co-Generative Nets

2019

In this paper, we propose Task-Adversarial co-Generative Nets (TAGN) for learning from multiple tasks. It aims to address the two fundamental issues of multi-task learning, i.e., domain shift and limited labeled data, in a principled …

Multiplex Graph Neural Network for Extractive Text Summarization

2021 · arXiv (Cornell University)

Extractive text summarization aims at extracting the most representative sentences from a given document as its summary. To extract a good summary from a long text document, sentence embedding plays an important role. Recent studies …

Backdoor Attack through Frequency Domain

2021 · arXiv (Cornell University)

Backdoor attacks have been shown to be a serious threat against deep learning systems such as biometric authentication and autonomous driving. An effective backdoor attack could enforce the model misbehave under certain predefined conditions, i.e., …

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

2023 · arXiv (Cornell University)

Finding node correspondence across networks, namely multi-network alignment, is an essential prerequisite for joint learning on multiple networks. Despite great success in aligning networks in pairs, the literature on multi-network alignment is sparse due to …

Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform

2024

Accessibility and openness are two of the most important factors in motivating AI and Web research. One example is as costs to train and deploy large Knowledge Graph (KG) systems increases, valuable auxiliary features such …

Few-Shot Knowledge Graph Completion via Transfer Knowledge from Similar Tasks

2025

Knowledge graphs (KGs) are essential in many AI applications but often suffer from incompleteness, limiting their utility. Many relations in KGs have only a few examples, making it challenging to train accurate models. Few-shot learning …

Neural-Answering Logical Queries on Knowledge Graphs

2021

Logical queries constitute an important subset of questions posed in knowledge graph question answering systems. Yet, effectively answering logical queries on large knowledge graphs remains a highly challenging problem. Traditional subgraph matching based methods might …