Jaewoo Kang

Learning User Preferences and Understanding Calendar Contexts for Event Scheduling

2018

With online calendar services gaining popularity worldwide, calendar data has become one of the richest context sources for understanding human behavior. However, event scheduling is still time-consuming even with the development of online calendars. Although …

Consistency Training with Virtual Adversarial Discrete Perturbation

2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Consistency training regularizes a model by enforcing predictions of original and perturbed inputs to be similar. Previous studies have proposed various augmentation methods for the perturbation but are limited in that they are agnostic to …

Co-Attention Graph Pooling for Efficient Pairwise Graph Interaction Learning

2023 · IEEE Access

Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data. However, previous works mainly focused on understanding single graph inputs while many real-world applications require pair-wise analysis for graph-structured …

Outlier-Safe Pre-Training for Robust 4-Bit Quantization of Large Language Models

2025 · arXiv (Cornell University)

Extreme activation outliers in Large Language Models (LLMs) critically degrade quantization performance, hindering efficient on-device deployment. While channel-wise operations and adaptive gradient scaling are recognized causes, practical mitigation remains challenging. We introduce Outlier-Safe Pre-Training (OSP), …

Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation

2018

Recommending a point-of-interest (POI) a user will visit next based on temporal and spatial context information is an important task in mobile-based applications. Recently, several POI recommendation models based on conventional sequential-data modeling approaches have …