331 citations · 610 across the 13 of their papers we have counts for
13 papers
Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8
Armstrong Aboah, Bin Wang, Ulas Bagci +1
Traffic safety is a major global concern. Helmet usage is a key factor in preventing head injuries and fatalities caused by motorcycle accidents. However, helmet usage violations c…
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…
Relational Sentence Embedding for Flexible Semantic Matching
Bin Wang, Haizhou Li
We present Relational Sentence Embedding (RSE), a new paradigm to further discover the potential of sentence embeddings. Prior work mainly models the similarity between sentences b…
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…
SynWMD: Syntax-aware Word Mover's Distance for Sentence Similarity Evaluation
Chengwei Wei, Bin Wang, C. -C. Jay Kuo
Word Mover's Distance (WMD) computes the distance between words and models text similarity with the moving cost between words in two text sequences. Yet, it does not offer good per…
Just Rank: Rethinking Evaluation with Word and Sentence Similarities
Bin Wang, C. -C. Jay Kuo, Haizhou Li
Word and sentence embeddings are useful feature representations in natural language processing. However, intrinsic evaluation for embeddings lags far behind, and there has been no…
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…
SBERT-WK: A Sentence Embedding Method by Dissecting BERT-based Word Models
Bin Wang, C. -C. Jay Kuo
Sentence embedding is an important research topic in natural language processing (NLP) since it can transfer knowledge to downstream tasks. Meanwhile, a contextualized word represe…
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…
Graph-based Deep-Tree Recursive Neural Network (DTRNN) for Text Classification
Fenxiao Chen, Bin Wang, C. -C. Jay Kuo
A novel graph-to-tree conversion mechanism called the deep-tree generation (DTG) algorithm is first proposed to predict text data represented by graphs. The DTG method can generate…
Post-Processing of Word Representations via Variance Normalization and Dynamic Embedding
Bin Wang, Fenxiao Chen, Angela Wang +1
Although embedded vector representations of words offer impressive performance on many natural language processing (NLP) applications, the information of ordered input sequences is…