A differentiable Sandpile Stabilization Layer (SSL) and congestion-aware objectives designed to redistribute excess load and manage stabilization costs are proposed and Experiments on long-range benchmarks show that targeting sandpile-identified bottlenecks mitigates representation collapse and improves over standard b...
Yang Shi, Li-Xian Chen, Jingchao Wang et al.· Proceedings of the 32nd ACM...· 0 citations
A rigorous Lipschitz analysis for constant curvature graph convolutional networks ( \(\kappa\) -GCNs) and enhances their robustness through Lipschitz regularization and derives upper bounds for the Lipschitz constants across constant curvature spaces, thereby standardizing the Lipschitz limits of the \(\kappa\) -stereo...
Yang Shi, Jingchao Wang, Liangsi Lu et al.· ACM Transactions on Knowledg...· 0 citations
Message-passing graph neural networks (MP-GNNs) are widely used for learning on relational data. However, their performance drops on tasks requiring long-range interactions due to over-squashing, where exponential information compression overwhelms fixed-width embeddings. While existing analyses often attribute this to...
Yang Shi, Lixian Chen, Jingchao Wang et al.· Proceedings of the 32nd ACM...· 0 citations
This approach combines local editing and background preservation without external or user-provided spatial masks and without model fine-tuning, and achieves the strongest reported preservation metrics, including 27.44~dB PSNR and 0.055 LPIPS.
Yang Shi, Liangsi Lu, Minzhe Guo et al.· 0 citations
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