6 citations · 16 across the 6 of their papers we have counts for
6 papers
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection
Jing Ren, Mingliang Hou, Zhixuan Liu +1
Graph anomaly detection is a popular and vital task in various real-world scenarios, which has been studied for several decades. Recently, many studies extending deep learning-base…
Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) Dataset
Zhixuan Liu, Youeun Shin, Beverley-Claire Okogwu +5
It has been shown that accurate representation in media improves the well-being of the people who consume it. By contrast, inaccurate representations can negatively affect viewers…
Towards Real-Time Text2Video via CLIP-Guided, Pixel-Level Optimization
Peter Schaldenbrand, Zhixuan Liu, Jean Oh
We introduce an approach to generating videos based on a series of given language descriptions. Frames of the video are generated sequentially and optimized by guidance from the CL…
A Neural-Symbolic Approach to Natural Language Understanding
Zhixuan Liu, Zihao Wang, Yuan Lin +1
Deep neural networks, empowered by pre-trained language models, have achieved remarkable results in natural language understanding (NLU) tasks. However, their performances can dras…
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Translation
Peter Schaldenbrand, Zhixuan Liu, Jean Oh
Generating images that fit a given text description using machine learning has improved greatly with the release of technologies such as the CLIP image-text encoder model; however,…
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Synthesis
Peter Schaldenbrand, Zhixuan Liu, Jean Oh
Generating images that fit a given text description using machine learning has improved greatly with the release of technologies such as the CLIP image-text encoder model; however,…