LLNL builds protein screening system that accelerates rare-earth separation using bacterial proteins and machine learning. US ...
To address AI bias at its roots, we must understand the human heuristics that shape it. Unlike prior frameworks that focus ...
Confidence is persuasive. In artificial intelligence systems, it is often misleading. Today's most capable reasoning models ...
To ensure a robust domestic supply chain in the U.S., Lawrence Livermore National Laboratory (LLNL) scientists are using ...
Wanted: a cheap, multipotent treatment for viral infections. Must be able to handle new or unfamiliar strains, or (even ...
The study, titled “GenAI-Powered Framework for Reliable Sentiment Labeling in Drug Safety Monitoring,” published in Applied ...
Million Records Built from Live Attack Traffic Released to Advance Cybersecurity Research at the University of ...
Abstract: Single positive multi-label learning (SPML) aims to recognize multiple categories with limited supervision from one positive label in an image. With the emergence of pre-trained ...
Stanford's 2026 AI Index: frontier models fail one in three attempts, lab transparency is declining, and benchmarks are ...
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 ...
Abstract: As a prominent research topic, multi-view multi-label classification (MvMlC) aims to assign multiple labels to samples by integrating information from various perspectives. However, in ...
In a recent experiment, researchers at UC Berkeley and UC Santa Cruz asked Google’s artificial intelligence model Gemini 3 to help clear up space on a computer system. This involved deleting a bunch ...
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