Seokhyun Lee

2 accepted papers

2026

INSHAPE: Instance-Level Shapelets for Interpretable Time-Series Classification

Seongjun Lee, Seokhyun Lee, Changhee Lee

IJCAI 2026

Discovering shapelets -- i.e., discriminative temporal patterns within time series -- has been widely studied to address the inherent complexity of time-series classification (TSC) and to make model decision-making processes more transparent. However, existing methods primarily focus on population-l

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2026

Position: AI Lock-In Is in Progress, and We Must Be Prepared

Jaeho Kim, Seokhyun Lee, Jieun Lee, Changhee Lee

ICML 2026spotlight

AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of generative AI's societal impacts (including unemployment risk and labor market disruption). However, an equally important dimension remains underexplored:…

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