Author

Moontae Lee

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#artificial intelligence Preprint Oct 2026

Continually Post-training Small Models via Synthetic Self-distillation

Continual post-training faces a dual challenge of acquisition and retention: models must learn new capabilities while preserving prior knowledge. While Self-Distillation Fine-Tuning (SDFT) mitigates this using self-supervision with in-context demonstrations, it relies on strong in-context learning and instruction-follo...

Woosung Koh, Hyunsoo Lee, Kyungjae Lee et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Program-Verified Self-Evolution for Vision-Language Models

Verifiable QA Generation for Self-Evolving Models (VQS) is presented, which changes how the model judges answers and improves Qwen3-VL by up to 3.18 points at the 2B, 4B, and 8B scales and outperforms the strongest self-evolving baseline at each.

Ahmed Heakl, Sungik Choi, Moontae Lee et al. · 0 citations