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title: "UASPL: Uncertainty-Aware Self-Paced Learning with Evidential Neural Networks — Stuff That Spins"
description: "arXiv:2607.06638v1 Announce Type: new Abstract: Self-paced learning (SPL) is an effective learning paradigm that simulates the human learning process by progre…"
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date: "2026-07-09T04:00:00+00:00"
modified: "2026-07-09T06:04:54.102958+00:00"
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# UASPL: Uncertainty-Aware Self-Paced Learning with Evidential Neural Networks

**Source:** Unknown  
**Published:** July 9, 2026  
**Original:** https://arxiv.org/abs/2607.06638  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.06638v1 Announce Type: new Abstract: Self-paced learning (SPL) is an effective learning paradigm that simulates the human learning process by progressing from easy to difficult samples based on the value of the loss function during the learning process. It has shown great potential in improving model performance and training efficiency. However, the prediction results of samples with smaller loss values are not necessarily reliable, indicating that such samples are not always simple s

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