3 papers
cs.LG2026
Towards On-Policy SFT: Distribution Discriminant Theory and its Applications in LLM Training
Miaosen Zhang, Yishan Liu, Shuxia Lin +8
Supervised fine-tuning (SFT) is computationally efficient but often yields inferior generalization compared to reinforcement learning (RL). This gap is primarily driven by RL's use…
cs.LG2026
The "Robert Boulton" Singularity: Semantic Tunneling and Manifold Unfolding in Recursive AI
Pengyue Hou
The stability of generative artificial intelligence trained on recursive synthetic data is conventionally monitored via Perplexity (PPL). We demonstrate that PPL is a deceptive met…
cs.CV2025
MUG-V 10B: High-efficiency Training Pipeline for Large Video Generation Models
Yongshun Zhang, Zhongyi Fan, Yonghang Zhang +6
In recent years, large-scale generative models for visual content (\textit{e.g.,} images, videos, and 3D objects/scenes) have made remarkable progress. However, training large-scal…