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Shao-Wei Chen

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#machine learning Preprint Sep 2026

Edge-Level Automorphism in GNNs: A Quantitative Framework and Effective Designs For Link Prediction

A novel quantitative framework to assess GNN expressiveness for link prediction is introduced, and the edge automorphism ratio (EAR) is introduced, a scalar metric that quantifies a GNN's ability to distinguish links in a given graph.

Shao-Wei Chen, Donald Loveland, Tobias Käfer et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Iris: Climbing to the Search Frontier

This work presents Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them, and plans to release the model weights together with the complete recipe for data construction, training, and evaluation.

Zi-Yuan Liu, He Liu, Zi-Chuan Wang et al. · 0 citations

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