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Desmond Higham

2 accepted papers

2026

Are we measuring oversmoothing in graph neural networks correctly?

ICLR 2026poster

Oversmoothing is a fundamental challenge in graph neural networks (GNNs): as the number of layers increases, node embeddings become increasingly similar, and model performance drops sharply. Traditionally, oversmoothing has been quantified using metrics that measure the similarity of neighbouring no…

Cited by 5SourceScholar
2024

Stealth edits to large language models

NeurIPS 2024poster

We reveal the theoretical foundations of techniques for editing large language models, and present new methods which can do so without requiring retraining. Our theoretical insights show that a single metric (a measure of the intrinsic dimension of the model's features) can be used to assess a model…