2 citations · 5 across the 7 of their papers we have counts for
8 papers
ReasonVQA: A Multi-hop Reasoning Benchmark with Structural Knowledge for Visual Question Answering
Duong T. Tran, Trung-Kien Tran, Manfred Hauswirth +1
In this paper, we propose a new dataset, ReasonVQA, for the Visual Question Answering (VQA) task. Our dataset is automatically integrated with structured encyclopedic knowledge and…
Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings
Yuqicheng Zhu, Nico Potyka, Bo Xiong +4
Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilisti…
Explaining Graph Neural Networks for Node Similarity on Graphs
Daniel Daza, Cuong Xuan Chu, Trung-Kien Tran +3
Similarity search is a fundamental task for exploiting information in various applications dealing with graph data, such as citation networks or knowledge graphs. While this task h…
VisionKG: Unleashing the Power of Visual Datasets via Knowledge Graph
Jicheng Yuan, Anh Le-Tuan, Manh Nguyen-Duc +3
The availability of vast amounts of visual data with heterogeneous features is a key factor for developing, testing, and benchmarking of new computer vision (CV) algorithms and arc…
CQELS 2.0: Towards A Unified Framework for Semantic Stream Fusion
Anh Le-Tuan, Manh Nguyen-Duc, Chien-Quang Le +4
We present CQELS 2.0, the second version of Continuous Query Evaluation over Linked Streams. CQELS 2.0 is a platform-agnostic federated execution framework towards semantic stream…
Fantastic Data and How to Query Them
Trung-Kien Tran, Anh Le-Tuan, Manh Nguyen-Duc +2
It is commonly acknowledged that the availability of the huge amount of (training) data is one of the most important factors for many recent advances in Artificial Intelligence (AI…
Faithiful Embeddings for EL++ Knowledge Bases
Bo Xiong, Nico Potyka, Trung-Kien Tran +2
Recently, increasing efforts are put into learning continual representations for symbolic knowledge bases (KBs). However, these approaches either only embed the data-level knowledg…
Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs
Medina Andresel, Trung-Kien Tran, Csaba Domokos +2
Current methods for embedding-based query answering over incomplete Knowledge Graphs (KGs) only focus on inductive reasoning, i.e., predicting answers by learning patterns from the…