31 citations · 48 across the 11 of their papers we have counts for
12 papers
Automatic Question-Answer Generation for Long-Tail Knowledge
Rohan Kumar, Youngmin Kim, Sunitha Ravi +4
Pretrained Large Language Models (LLMs) have gained significant attention for addressing open-domain Question Answering (QA). While they exhibit high accuracy in answering question…
Multimodal Graph Learning for Generative Tasks
Minji Yoon, Jing Yu Koh, Bryan Hooi +1
Multimodal learning combines multiple data modalities, broadening the types and complexity of data our models can utilize: for example, from plain text to image-caption pairs. Most…
Graph Generative Model for Benchmarking Graph Neural Networks
Minji Yoon, Yue Wu, John Palowitch +2
As the field of Graph Neural Networks (GNN) continues to grow, it experiences a corresponding increase in the need for large, real-world datasets to train and test new GNN models o…
A Dataset on Malicious Paper Bidding in Peer Review
Steven Jecmen, Minji Yoon, Vincent Conitzer +2
In conference peer review, reviewers are often asked to provide "bids" on each submitted paper that express their interest in reviewing that paper. A paper assignment algorithm the…
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks
Minji Yoon, John Palowitch, Dustin Zelle +3
Data continuously emitted from industrial ecosystems such as social or e-commerce platforms are commonly represented as heterogeneous graphs (HG) composed of multiple node/edge typ…
Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off
Minji Yoon, Théophile Gervet, Bryan Hooi +1
Graph data is ubiquitous in academia and industry, from social networks to bioinformatics. The pervasiveness of graphs today has raised the demand for algorithms that can answer va…
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach
Minji Yoon, Bryan Hooi, Kijung Shin +1
Given a dynamic graph stream, how can we detect the sudden appearance of anomalous patterns, such as link spam, follower boosting, or denial of service attacks? Additionally, can w…
Real-Time Anomaly Detection in Edge Streams
Siddharth Bhatia, Rui Liu, Bryan Hooi +3
Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant tim…
MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams
Siddharth Bhatia, Bryan Hooi, Minji Yoon +2
Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant tim…
Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees
Minji Yoon, Woojeong Jin, U Kang
Given a time-evolving graph, how can we track similarity between nodes in a fast and accurate way, with theoretical guarantees on the convergence and the error? Random Walk with Re…
PMV: Pre-partitioned Generalized Matrix-Vector Multiplication for Scalable Graph Mining
Chiwan Park, Ha-Myung Park, Minji Yoon +1
How can we analyze enormous networks including the Web and social networks which have hundreds of billions of nodes and edges? Network analyses have been conducted by various graph…
TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs
Minji Yoon, Jinhong Jung, U Kang
Given a large graph, how can we determine similarity between nodes in a fast and accurate way? Random walk with restart (RWR) is a popular measure for this purpose and has been exp…