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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Lequan Lin

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Open access Nov 2023

Exposition on Over-Squashing Problem of GNNs: Current Methods, Benchmarks and Challenges

Graph-based message-passing neural networks (MPNNs) have achieved remarkable success in both node and graph-level tasks. However, several identified problems, including over-smoothing (OSM), limited expressive power, and over-squashing (OSQ), still restrain the performance of MPNNs. In particular, the latest identified...

Dai Shi, Andi Han, Le-Quan Lin et al. · 26 citations · ⚡1
#machine learning Preprint Sep 2026

SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration

SupportCal is introduced, a label-free post-hoc method that retains agreement examples at unit weight and assigns disagreement examples continuous weights based on the own-base PLM's relative support and corroboration from pretrained references selected from a size-compatible candidate pool.

Linhan Luo, Le-Quan Lin, Dai Shi et al. · 0 citations
Open access Aug 2026

Exposition on Over-squashing Problem of GNNs: Current Methods, Benchmarks and Challenges.

This work presents an exposition of the OSQ problem by summarizing its various formulations in the current literature and categorizing existing solutions into three different types, and summarizes the empirical methods proposed by existing works to verify the efficiency of OSQ mitigation approaches.

Dai Shi, Andi Han, Lequan Lin et al. · 0 citations

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