Author

D. Nguyen

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#artificial intelligence May 2026

Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression

This work introduces a distributional framework for SAE analyses, in which each feature is represented not by a single decoder vector like in the literature, but by an activation-weighted distribution over the hidden states that express it, and provides a unified semantic metric for cross-layer feature comparison.

T. M. Cao, D. Nguyen, My T. Thai · arXiv.org · 2 citations

#artificial intelligence Preprint Sep 2026

HARMONIA: Interpretable Graph Learning through Mixtures of Neural Bases

HARMONIA achieves stronger explanation recovery than existing interpretable graph baselines while maintaining competitive predictive performance and scaling to graphs with millions of nodes, and shows that interpretable graph learning can remain both faithful and scalable without sacrificing predictive effectiveness.

Q. D. Bùi, D. Nguyen, A. Dang et al. · 0 citations

#machine learning Preprint Sep 2026

RAPTOR: Role-Aware Private Training for Mixture-of-Experts

This work introduces RAPTOR - a Role-Aware Private Training framework, which alternates shared and expert optimization and targets each failure directly, using expert-specific clipping and noise together with a public expected-owner denominator and a count-independent update schedule that avoids conditioning on private...

Duc Dm, Khai Le-Duc, D. Nguyen et al. · 0 citations