Unite.AI

The Scheming Problem: Why Advanced AI Models Are Learning to Hide Their True Goals

For years, the AI community has worked to make systems not just more capable, but more aligned with human values. Researchers have developed training methods to ensure models follow instructions, ...
Tech Xplore

Emoticons can confuse LLMs, causing 'silent failures' in coding responses

Large language models (LLMs), artificial intelligence (AI) systems that can process and generate texts in various languages, ...
IEEE

Federated Semi-Supervised Learning with Annotation Heterogeneity

Abstract: Federated Semi-Supervised Learning (FSSL) aims to learn a global model from different clients in an environment with both labeled and unlabeled data. Most of the existing FSSL work generally ...
InfoWorld

Improving annotation quality with machine learning

Data science and machine learning teams face a hidden productivity killer: annotation errors. Recent research from Apple analyzing production machine learning (ML ...
C&EN

Metabolite Identification Data in Drug Discovery, Part 2: Site-of-Metabolism Annotation, Analysis, and Exploration for Machine Learning

Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Medicinal Chemistry, Research ...