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Ziniu Liu

2 accepted papers

2026

Enhancing Logical Expressiveness in Graph Neural Networks via Path-Neighbor Aggregation

AAAI 2026technical

Graph neural networks (GNNs) can effectively model structural information of graphs, making them widely used in knowledge graph (KG) reasoning. However, existing studies on the expressive power of GNNs mainly focuses on simple single-relation graphs, and there is still insufficient discussion on the

Cited by 0SourcePDFScholar
2026

MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene

CVPR 2026

Generalizable Neural Radiance Fields (GeNeRF) enable high-quality scene reconstruction from a limited number of views and can generalize to unseen scenes. However, in real-world environments, transient distractors disrupt structural consistency across views, leading to deviated supervision signals a

Cited by 0SourcecodeScholar