331 citations · 665 across the 20 of their papers we have counts for
20 papers
Efficient Human-Object-Interaction (EHOI) Detection via Interaction Label Coding and Conditional Decision
Tsung-Shan Yang, Yun-Cheng Wang, Chengwei Wei +2
Human-Object Interaction (HOI) detection is a fundamental task in image understanding. While deep-learning-based HOI methods provide high performance in terms of mean Average Preci…
GSBIQA: Green Saliency-guided Blind Image Quality Assessment Method
Zhanxuan Mei, Yun-Cheng Wang, C. -C. Jay Kuo
Blind Image Quality Assessment (BIQA) is an essential task that estimates the perceptual quality of images without reference. While many BIQA methods employ deep neural networks (D…
Word Embedding Dimension Reduction via Weakly-Supervised Feature Selection
Jintang Xue, Yun-Cheng Wang, Chengwei Wei +1
As a fundamental task in natural language processing, word embedding converts each word into a representation in a vector space. A challenge with word embedding is that as the voca…
GreenSaliency: A Lightweight and Efficient Image Saliency Detection Method
Zhanxuan Mei, Yun-Cheng Wang, C. -C. Jay Kuo
Image saliency detection is crucial in understanding human gaze patterns from visual stimuli. The escalating demand for research in image saliency detection is driven by the growin…
Knowledge Graph Embedding: An Overview
Xiou Ge, Yun-Cheng Wang, Bin Wang +1
Many mathematical models have been leveraged to design embeddings for representing Knowledge Graph (KG) entities and relations for link prediction and many downstream tasks. These…
Bias and Fairness in Chatbots: An Overview
Jintang Xue, Yun-Cheng Wang, Chengwei Wei +3
Chatbots have been studied for more than half a century. With the rapid development of natural language processing (NLP) technologies in recent years, chatbots using large language…
AsyncET: Asynchronous Learning for Knowledge Graph Entity Typing with Auxiliary Relations
Yun-Cheng Wang, Xiou Ge, Bin Wang +1
Knowledge graph entity typing (KGET) is a task to predict the missing entity types in knowledge graphs (KG). Previously, KG embedding (KGE) methods tried to solve the KGET task by…
An Overview on Generative AI at Scale with Edge-Cloud Computing
Yun-Cheng Wang, Jintang Xue, Chengwei Wei +1
As a specific category of artificial intelligence (AI), generative artificial intelligence (GenAI) generates new content that resembles what is created by humans. The rapid develop…
Blind Video Quality Assessment at the Edge
Zhanxuan Mei, Yun-Cheng Wang, C. -C. Jay Kuo
Owing to the proliferation of user-generated videos on the Internet, blind video quality assessment (BVQA) at the edge attracts growing attention. The usage of deep-learning-based…
Knowledge Graph Embedding with 3D Compound Geometric Transformations
Xiou Ge, Yun-Cheng Wang, Bin Wang +1
The cascade of 2D geometric transformations were exploited to model relations between entities in a knowledge graph (KG), leading to an effective KG embedding (KGE) model, Compound…
Lightweight High-Performance Blind Image Quality Assessment
Zhanxuan Mei, Yun-Cheng Wang, Xingze He +2
Blind image quality assessment (BIQA) is a task that predicts the perceptual quality of an image without its reference. Research on BIQA attracts growing attention due to the incre…
An Overview on Language Models: Recent Developments and Outlook
Chengwei Wei, Yun-Cheng Wang, Bin Wang +1
Language modeling studies the probability distributions over strings of texts. It is one of the most fundamental tasks in natural language processing (NLP). It has been widely used…
GreenKGC: A Lightweight Knowledge Graph Completion Method
Yun-Cheng Wang, Xiou Ge, Bin Wang +1
Knowledge graph completion (KGC) aims to discover missing relationships between entities in knowledge graphs (KGs). Most prior KGC work focuses on learning embeddings for entities…
CompoundE: Knowledge Graph Embedding with Translation, Rotation and Scaling Compound Operations
Xiou Ge, Yun-Cheng Wang, Bin Wang +1
Translation, rotation, and scaling are three commonly used geometric manipulation operations in image processing. Besides, some of them are successfully used in developing effectiv…
GreenBIQA: A Lightweight Blind Image Quality Assessment Method
Zhanxuan Mei, Yun-Cheng Wang, Xingze He +1
Deep neural networks (DNNs) achieve great success in blind image quality assessment (BIQA) with large pre-trained models in recent years. Their solutions cannot be easily deployed…
CORE: A Knowledge Graph Entity Type Prediction Method via Complex Space Regression and Embedding
Xiou Ge, Yun-Cheng Wang, Bin Wang +1
Entity type prediction is an important problem in knowledge graph (KG) research. A new KG entity type prediction method, named CORE (COmplex space Regression and Embedding), is pro…
KGBoost: A Classification-based Knowledge Base Completion Method with Negative Sampling
Yun-Cheng Wang, Xiou Ge, Bin Wang +1
Knowledge base completion is formulated as a binary classification problem in this work, where an XGBoost binary classifier is trained for each relation using relevant links in kno…
Efficient Sentence Embedding via Semantic Subspace Analysis
Bin Wang, Fenxiao Chen, Yuncheng Wang +1
A novel sentence embedding method built upon semantic subspace analysis, called semantic subspace sentence embedding (S3E), is proposed in this work. Given the fact that word embed…
Graph Representation Learning: A Survey
Fenxiao Chen, Yuncheng Wang, Bin Wang +1
Research on graph representation learning has received a lot of attention in recent years since many data in real-world applications come in form of graphs. High-dimensional graph…
Evaluating Word Embedding Models: Methods and Experimental Results
Bin Wang, Angela Wang, Fenxiao Chen +2
Extensive evaluation on a large number of word embedding models for language processing applications is conducted in this work. First, we introduce popular word embedding models an…