Self-regulation can curb students' overconfidence in AI

The rapid emergence of generative AI in higher education has raised concerns about students' reliance on the use of these ...
IEEE

Contrastive Self-Supervised Learning-Based Background Reconstruction for Hyperspectral Anomaly Detection

Abstract: Deep learning (DL) has received a lot of attention in hyperspectral anomaly detection (HAD) in recent years. While some progress has been made in boosting the generalization of DL-based HAD ...
Frontiers

Generative AI in Education: Cognitive Mechanisms, Learning Outcomes, and Evidence-Based Practice

The rapid adoption of generative AI tools — including large language models such as ChatGPT, DeepSeek, and domain-specific tutoring systems — has outpaced ...

LLMs believe false statements even after explicit warnings that they’re false

New research on so-called “negation neglect” finds that LLMs in a roughly analogous situation don’t behave that way. They ...
IEEE

Self-Supervised Feature Learning for Cardiac Cine MR Image Reconstruction

Abstract: We propose a self-supervised feature learning assisted reconstruction (SSFL-Recon) framework for MRI reconstruction to address the limitation of existing supervised learning methods.
GitHub

plot_label_propagation_structure.py

# We generate a dataset with two concentric circles. In addition, a label # is associated with each sample of the dataset that is: 0 (belonging to # the outer circle), 1 (belonging to the inner circle ...
GitHub

Label Propagation digits: Active learning

then we select the top five most uncertain points to label. Next, we train with 15 labeled points (original 10 + 5 new ones). We repeat this process four times to have a model trained with 30 labeled ...