Science

New research explores whether large language models can accurately identify and interpret the complex values embedded within qualitative interview data.

New research reveals how the popular ReLU activation function subtly influences the solutions found by gradient descent in high-dimensional neural networks.

Researchers are leveraging the power of self-supervised learning and efficient model tuning to create authentic maritime radio dialogues, overcoming the limitations of scarce real-world data.

Researchers have developed a novel loss function that improves forecasting accuracy by addressing inherent biases in how models predict patterns over time and space.

A novel framework leverages inexpensive labels and self-supervision to enhance the robustness and efficiency of surrogate-based optimization for complex problems.

A new framework uses a dynamic, agent-based approach to carefully order math problems, dramatically improving how efficiently artificial intelligence learns to reason.

A new deep generative framework dramatically speeds up Bayesian analysis of complex datasets, unlocking more accurate insights from the cosmic microwave background.

Researchers are leveraging the limitations of censored language models to build a unique testing ground for eliciting truthful responses and identifying falsehoods.

New research reveals that large language models are capable of generating persuasive, propagandistic content, raising concerns about the potential for automated misinformation.

Researchers are harnessing the power of artificial intelligence to identify the subtle linguistic cues that indicate belief in conspiracy theories and understand how these ideas spread.