Beyond the Hype: Smarter Fake News Detection with Common Sense

A new framework, FactGuard, tackles the challenge of fake news by integrating commonsense reasoning and mitigating stylistic biases in large language models.

A new framework, FactGuard, tackles the challenge of fake news by integrating commonsense reasoning and mitigating stylistic biases in large language models.

Researchers are combining the strengths of logic programming and deep learning to build machine learning models that are both accurate and demonstrably fair.
New research reveals that even small changes to numerical values within factual claims can significantly impact the accuracy of large language models’ veracity predictions.

A new study rigorously assesses how well artificial intelligence, particularly large language models, can identify and flag malicious phishing attempts.
A new loss function tackles the inherent uncertainty in time series data to deliver more accurate predictions.

A new serverless architecture efficiently handles the demands of graph neural network-based intrusion detection, delivering low latency and high scalability.

New research employs physics-informed neural networks to investigate a modified dark energy model, offering a potential path towards resolving the ongoing discrepancy in the universe’s expansion rate.

Researchers are harnessing the power of advanced artificial intelligence to bridge the gap between observations of the Sun and the resulting conditions in space around Earth.

Researchers have unveiled a powerful new model capable of understanding and reasoning about music with unprecedented accuracy, pushing the boundaries of what’s possible in audio-based artificial intelligence.

Researchers are exploring attention mechanisms inspired by the brain to build more efficient and expressive models for processing sequential data.