Author

Peng Hu

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#machine learning Preprint Sep 2026

NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts

This paper proposes NeuCME, a novel framework designed to effectively learn and integrate knowledge across tasks with varying modalities, and formulate an evaluation metric to quantify the dynamism of task sequences and then set up a comprehensive benchmark with different degrees of dynamism.

Kai Guo, Chuan-Bin Liu, Peng Hu et al. · 0 citations

Jul 2026

Robust Losses from Univariate Base Functions for Noisy-Label Learning

A general framework that constructs robust multiclass losses from univariate base functions by defining mapping operators from base functions to multiclass losses, so that the robustness of the induced losses can be characterized through simple properties of the base functions.

Peng Hu, Jian-Wei Ma · arXiv.org · 0 citations