57 citations · 184 across the 33 of their papers we have counts for
34 papers
ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning
Linhao Luo, Jiaxin Ju, Bo Xiong +3
Logical rules are essential for uncovering the logical connections between relations, which could improve reasoning performance and provide interpretable results on knowledge graph…
Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain
Fatemeh Shiri, Teresa Wang, Shirui Pan +5
International maritime crime is becoming increasingly sophisticated, often associated with wider criminal networks. Detecting maritime threats by means of fusing data purely relate…
Shedding Light on Rechargeable Na/Cl Battery
Guanzhou Zhu, Peng Liang, Cheng-Liang Huang +9
Advancing new ideas of rechargeable batteries represents an important path to meeting the ever increasing energy storage needs. Recently we showed rechargeable sodium/chlorine (Na/…
Visual Subtitle Feature Enhanced Video Outline Generation
Qi Lv, Ziqiang Cao, Wenrui Xie +10
With the tremendously increasing number of videos, there is a great demand for techniques that help people quickly navigate to the video segments they are interested in. However, c…
Structured Two-stream Attention Network for Video Question Answering
Lianli Gao, Pengpeng Zeng, Jingkuan Song +4
To date, visual question answering (VQA) (i.e., image QA and video QA) is still a holy grail in vision and language understanding, especially for video QA. Compared with image QA t…
Paraphrasing Techniques for Maritime QA system
Fatemeh Shiri, Terry Yue Zhuo, Zhuang Li +5
There has been an increasing interest in incorporating Artificial Intelligence (AI) into Defence and military systems to complement and augment human intelligence and capabilities.…
An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers
Yong-Bin Kang, Abdur Rahim Mohammad Forkan, Prem Prakash Jayaraman +5
There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digit…
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming
Yizhen Zheng, Ming Jin, Shirui Pan +4
Graph representation learning (GRL) is critical for graph-structured data analysis. However, most of the existing graph neural networks (GNNs) heavily rely on labeling information,…
Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model
Sheng Bi, Xiya Cheng, Yuan-Fang Li +5
The ability to generate natural-language questions with controlled complexity levels is highly desirable as it further expands the applicability of question generation. In this pap…
Improving Numerical Reasoning Skills in the Modular Approach for Complex Question Answering on Text
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Numerical reasoning skills are essential for complex question answering (CQA) over text. It requires opertaions including counting, comparison, addition and subtraction. A successf…
Semantic Compositional Learning for Low-shot Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Scene graphs provide valuable information to many downstream tasks. Many scene graph generation (SGG) models solely use the limited annotated relation triples for training, leading…
Exploiting Scene Graphs for Human-Object Interaction Detection
Tao He, Lianli Gao, Jingkuan Song +1
Human-Object Interaction (HOI) detection is a fundamental visual task aiming at localizing and recognizing interactions between humans and objects. Existing works focus on the visu…
Unsupervised Domain-adaptive Hash for Networks
Tao He, Lianli Gao, Jingkuan Song +1
Abundant real-world data can be naturally represented by large-scale networks, which demands efficient and effective learning algorithms. At the same time, labels may only be avail…
Semi-supervised Network Embedding with Differentiable Deep Quantisation
Tao He, Lianli Gao, Jingkuan Song +1
Learning accurate low-dimensional embeddings for a network is a crucial task as it facilitates many downstream network analytics tasks. For large networks, the trained embeddings o…
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
Tahmid Hasan, Abhik Bhattacharjee, Md Saiful Islam +5
Contemporary works on abstractive text summarization have focused primarily on high-resource languages like English, mostly due to the limited availability of datasets for low/mid-…
Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection
Shirong Shen, Tongtong Wu, Guilin Qi +3
Event detection (ED) aims at detecting event trigger words in sentences and classifying them into specific event types. In real-world applications, ED typically does not have suffi…
Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning
Ming Jin, Yizhen Zheng, Yuan-Fang Li +3
Graph representation learning plays a vital role in processing graph-structured data. However, prior arts on graph representation learning heavily rely on labeling information. To…
Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction
Bhagya Hettige, Weiqing Wang, Yuan-Fang Li +2
Predicting (1) when the next hospital admission occurs and (2) what will happen in the next admission about a patient by mining electronic health record (EHR) data can provide gran…
Curriculum-Meta Learning for Order-Robust Continual Relation Extraction
Tongtong Wu, Xuekai Li, Yuan-Fang Li +4
Continual relation extraction is an important task that focuses on extracting new facts incrementally from unstructured text. Given the sequential arrival order of the relations, t…
Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Bases
Sheng Bi, Xiya Cheng, Yuan-Fang Li +2
Question generation over knowledge bases (KBQG) aims at generating natural-language questions about a subgraph, i.e. a set of (connected) triples. Two main challenges still face th…
Understanding Unnatural Questions Improves Reasoning over Text
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Complex question answering (CQA) over raw text is a challenging task. A prominent approach to this task is based on the programmer-interpreter framework, where the programmer maps…
Code2Que: A Tool for Improving Question Titles from Mined Code Snippets in Stack Overflow
Zhipeng Gao, Xin Xia, David Lo +2
Stack Overflow is one of the most popular technical Q&A sites used by software developers. Seeking help from Stack Overflow has become an essential part of software developers' dai…
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Despite the huge progress in scene graph generation in recent years, its long-tail distribution in object relationships remains a challenging and pestering issue. Existing methods…
Generating Question Titles for Stack Overflow from Mined Code Snippets
Zhipeng Gao, Xin Xia, John Grundy +2
Stack Overflow has been heavily used by software developers as a popular way to seek programming-related information from peers via the internet. The Stack Overflow community recom…