MACHINE-LEARNING models can distinguish children with autism spectrum disorder (ASD) from their typically developing (TD) peers using eye-tracking technology with 85% accuracy, a 2026 systematic ...

In this tutorial, we implement a Colab-ready version of the AutoResearch framework originally proposed by Andrej Karpathy. We build an automated experimentation pipeline that clones the AutoResearch ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Eye-tracking (ET) provides fine-grained, real-time indicators of how school-age students allocate visual attention during learning, yet its translation into school-based assessment and intervention ...

Researchers at Qingdao University in China have developed a lightweight, self-powered eye-tracking system designed to assist individuals with severe mobility impairments. Today, eye-tracking ...

Mobile eye-tracking is a valuable method that holds significant potential for understanding informal learning in applied environmental science settings, yet it remains underutilized. In this paper, we ...

Abstract: Catching eye diseases early on makes a huge difference. Things like diabetic retinopathy, glaucoma, cataract, and age-related macular degeneration can lead to serious vision loss if not ...

Numerous models have been developed for scanpath and saliency prediction, which are typically trained on scanpaths, which model eye movement as a sequence of discrete fixation points connected by ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has introduced Nested Learning, a ...