arXiv Machine Learning August 17, 2026 By A. Quadir, A. Rahaman, Mushir Akhtar, M. Tanveer

Robust Dual-Model Collaborative Random Vector Functional Link Network

Read the original on arXiv Machine Learning →

arXiv:2608. 13628v1 Announce Type: new Abstract: Random vector functional link (RVFL) networks are lightweight and fast neural models that offer efficient training and strong generalization through randomized hidden-layer weights and direct input-output connections.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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arXiv Machine Learning

Jul 28

XGRVFL-MV: Residual-Coupled Graph-Embedded Multi-View Random Vector Functional Link Network with FleXi Guardian Loss

arXiv:2607. 23149v1 Announce Type: new Abstract: Random Vector Functional Link (RVFL) networks provide an efficient randomized learning framework for classification.

By Yogesh Kumar, Mudasir Ganaie

rag benchmarks

arXiv Machine Learning

Jun 2

Sensitivity as a Double-Edged Sword: A Trade-off Between Discriminability and Adversarial Robustness

arXiv:2606. 01746v1 Announce Type: cross Abstract: Modern neural networks are highly susceptible to adversarial perturbations.

By Kai Wang

fine-tuning benchmarks safety

arXiv Machine Learning

Jul 27

A Leakage-Free Stacked Ensemble Method for Multiclass Classification

arXiv:2607. 22081v1 Announce Type: new Abstract: Multiclass classification is a fundamental problem across a wide range of domains.

By S. P. Sharmila, Aruna Tiwari

arXiv AI

Jun 16

ALCL: An Adaptive Log-Correntropy Loss for Robust Learning under Non-Gaussian Noise

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By Mainak Kundu, Ria Kanjilal, Ismail Uysal

benchmarks

arXiv Machine Learning

Jul 27

Smart predict-then-robustly-optimize

arXiv:2607. 21773v1 Announce Type: new Abstract: In this paper, we propose and study a robust variant of the smart predict-then-optimize approach that accounts for prediction shifts due to disturbance in the covariate feature space.

By Aakil Caunhye, Xuefei Lu, Belen Martin-Barragan

arXiv AI

Jul 15

Sparse Autoencoders for Interpretable Out-of-Distribution Detection

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By Ayush Karmacharya (Purdue University), Luke Luschwitz (Purdue University), Lucia Romero (Purdue University), Yanan Niu (EPFL), Joseph Campbell (Purdue University)

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XGRVFL-MV: Residual-Coupled Graph-Embedded Multi-View Random Vector Functional Link Network with FleXi Guardian Loss

Sensitivity as a Double-Edged Sword: A Trade-off Between Discriminability and Adversarial Robustness

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