3 papers
cs.AI2026
TimeTok: Granularity-Controllable Time-Series Generation via Hierarchical Tokenization
Seokhyun Lee, Jaeho Kim, Changjun Oh +2
Time-series generative models often lack control over temporal granularity, forcing users to accept whatever granularity the model produces. To enable truly user-driven generation,…
cs.LG2025
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
Jaeho Kim, Seulki Lee
Unsupervised domain adaptation (UDA) for time series data remains a critical challenge in deep learning, with traditional pseudo-labeling strategies failing to capture temporal pat…
cs.AI2025
Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
Jaeho Kim, Yunseok Lee, Seulki Lee
The peer review process in major artificial intelligence (AI) conferences faces unprecedented challenges with the surge of paper submissions (exceeding 10,000 submissions per venue…