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Dongbin Kim

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Preprint Aug 2026

A Locally Tokenized Generative Model for Robust Time-Series Watermarking

Watermarking is a central tool for provenance in generative models, yet its application to multivariate time series remains hindered by reliability failures under post-editing attacks. We show that existing detectors, which rely on globally coupled re-encoding, suffer from bidirectional drift of the null distribution:...

Dongbin Kim, Geonwoo Shin, Yujin Choi et al. · 0 citations
#artificial intelligence Preprint Aug 2026

Discretizing Continuous Time Series for Imputation with Masked Diffusion Training

The Masked Diffusion Time-series Imputation Model (MDTIM) is proposed, which leverages the training paradigm of masked diffusion model for imputation tasks, and introduces Stochastic Discretization, which maps continuous values to ordinal-aware tokens while preserving continuous dynamics.

Dongbin Kim, Seungyun Lee, Geonwoo Shin et al. · 0 citations

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