D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training 事件

D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training arXiv:2605.31164v1 Announce Type: new Abstract: Training data plays a central role in large language models (LLMs) optimization, motivating extensive research on data scheduling strategies. Most existing approaches concentrate on adjusting the overall data distribution but neglect the underlying interactions between samples during training. However, we argue that such interactions cannot be overlooked, as real-world d