Tech Xplore

This AI mines the numbers buried in scientific papers and turns them into usable data fast

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.
Virtualization Review

AI on a Raspberry Pi: Part 3 -- Testing Different LLMs

Benchmarking four compact LLMs on a Raspberry Pi 500+ shows that smaller models such as TinyLlama are far more practical for local edge workloads, while reasoning-focused models trade latency for ...

Frontier models are failing one in three production attempts — and getting harder to audit

Stanford's 2026 AI Index: frontier models fail one in three attempts, lab transparency is declining, and benchmarks are ...
IEEE

Classification of Cognitive Load Using Deep Learning Based on Eye Movement Indices

Abstract: The classification of cognitive load is crucial to evaluate mental effort in various tasks. Compared to physiological measures such as electroencephalography (EEG), electrocardiography (ECG) ...
eLife

New idtracker.ai rethinks multi-animal tracking as a representation learning problem to increase accuracy and reduce tracking time

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.
Journal of Medical Internet Research

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review

No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution ...
IEEE

WonderTex: Consistent-and-Seamless Texture Generation with Text-Guided Multi-View Image Diffusion Models

Abstract: Text-guided texture generation has been rapidly developed with the proliferation of generative artificial intelligence for creating three-dimensional textured objects. However, existing text ...