Author

Jin-Kwan Jang

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#artificial intelligence Preprint Jan 2026

What If TSF: Reframing Time Series Forecasting as Scenario-Guided Multimodal Forecasting

This work introduces What If TSF (WIT), a benchmark for evaluating whether models effectively respond to future scenarios, and shows that factual accuracy gains do not consistently translate into appropriate responses to alternative scenarios, demonstrating the need to evaluate multimodal forecasting beyond predictive...

Jin-Kwan Jang, Hyunbin Jin, Hyungjin Park et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Interweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models

This work studies training-free coupling of frozen TSFM marginals into multivariate forecast sample paths, finding the same pattern persists when the fixed-marginal constraint is removed and paths are sampled directly, and remains present under native multivariate backbone inference.

Jinmyeong Choi, Jin-Kwan Jang, Seul Lee et al. · 0 citations