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Continually Post-training Small Models via Synthetic Self-distillation
Woosung Koh, Hyunsoo Lee, Kyungjae Lee +4
Continual post-training faces a dual challenge of acquisition and retention: models must learn new capabilities while preserving prior knowledge. While Self-Distillation Fine-Tunin…
Language Models Can Control Their Own Attention
Namgyu Ho, Huzama Ahmad, Woosung Koh +3
Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If the user asks about a previou…
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
Woosung Koh, Jeyoung Jeon, Youngjin Song +4
Current language model training commonly applies multi-task Supervised Fine-Tuning (SFT) using a homogeneous compute budget across all sub-datasets. This approach is fundamentally…
Generative Visual Code Mobile World Models
Woosung Koh, Sungjun Han, Segyu Lee +2
Mobile Graphical User Interface (GUI) World Models (WMs) offer a promising path for improving mobile GUI agent performance at train- and inference-time. However, current approaches…