2 papers
cs.LG2026
Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement
Guoming Li, Jian Yang, Xukun Wang +3
Coarsening-based training for graph neural networks (GNNs), i.e.\ training on coarsened graphs rather than the original large ones, has become a promising direction for scaling GNN…
cs.LG2025
Test-Time Scaling with Reflective Generative Model
Zixiao Wang, Yuxin Wang, Xiaorui Wang +8
We introduce our first reflective generative model MetaStone-S1, which obtains OpenAI o3-mini's performance via the new Reflective Generative Form. The new form focuses on high-qua…