1 citations · 1 across the 4 of their papers we have counts for
4 papers
Causal Behavioral Evaluation of AI Agents at Scale via Automated Behavioral Science
Soo Yong Lee, Jongha Lee, Jaewan Chun +8
As AI agents are increasingly deployed in complex and new environments, knowing the conditions that influence their behavior becomes an indispensable step for their reliable and sa…
Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts
Jongha Lee, Taehyung Kwon, Heechan Moon +1
The problem of predicting node properties (e.g., node classes) in graphs has received significant attention due to its broad range of applications. Graphs from real-world datasets…
TiGer: Self-Supervised Purification for Time-evolving Graphs
Hyeonsoo Jo, Jongha Lee, Fanchen Bu +1
Time-evolving graphs, such as social and citation networks, often contain noise that distorts structural and temporal patterns, adversely affecting downstream tasks, such as node c…
SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning
Jongha Lee, Sunwoo Kim, Kijung Shin
To detect anomalies in real-world graphs, such as social, email, and financial networks, various approaches have been developed. While they typically assume static input graphs, mo…