Su-Hyeon Kim — accepted AI-conference papers

2026

ReSyn: A Generalized Recursive Regular Expression Synthesis Framework

Seongmin Kim, Hyunjoon Cheon, Su-Hyeon Kim, Yo-Sub Han, Sang-Ki Ko

IJCAI 2026

Existing Programming-By-Example (PBE) systems often rely on simplified benchmarks that fail to capture the high structural complexity—such as deeper nesting and frequent Unions—of real-world regexes. To overcome the resulting performance drop, we propose ReSyn, a synthesizer-agnostic divide-and-conq

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2023

GDA: Grammar-based Data Augmentation for Text Classification using Slot Information

Joonghyuk Hahn, Hyunjoon Cheon, Elizabeth Grace Orwig, Su-Hyeon Kim, Sang-Ki Ko, Yo-Sub Han

EMNLP 2023long findings

Recent studies propose various data augmentation approaches to resolve the low-resource problem in natural language processing tasks. Data augmentation is a successful solution to this problem and recent strategies give variation on sentence structures to boost performance. However, these approaches…

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