Science

Researchers are leveraging the power of deep learning to identify and block command-and-control traffic from malware using algorithmically generated domain names.

Researchers have developed a novel counterfactual analysis method for spectrum auctions that proves incorporating deployment obligations can expand broadband access without sacrificing revenue.

Researchers are using explainable AI to pinpoint and correct imperfections in images created by diffusion models, leading to more realistic and refined results.

Researchers are boosting the resilience of deepfake detectors with a novel training technique that improves performance and efficiency across a wide range of generated content.

A new technique boosts the accuracy of information retrieval from complex financial filings by leveraging large language models to improve semantic search.

A new framework leverages specialized learning and structural analysis to provide more human-centric explanations for how graph neural networks arrive at their decisions.

A new machine learning approach predicts cryptocurrency performance by ranking assets, offering a potential edge over traditional investment strategies.

A new study explores whether traditional text summarization techniques can hold their own against the rising dominance of large language models in the financial news landscape.

A new machine learning framework analyzes international trade data to identify suspicious activity related to ozone-depleting substances and their replacements.

A new model combines the power of financial news analysis with historical stock data to deliver more accurate predictions than traditional methods.