Science

Researchers are leveraging the power of large language models to identify misleading information in the financial world, achieving top results in a recent challenge.

New research reveals that acoustic features in corporate earnings calls are surprisingly unreliable for gauging financial health, and can even hinder predictive accuracy.

A new deep learning framework improves the accuracy of building load forecasting by intelligently fusing historical data and adapting to fluctuating energy usage.

A novel deep learning model leverages the power of CNNs, LSTMs, and attention to accurately forecast when industrial equipment will fail, prioritizing safety and minimizing downtime.

Reusable skills for AI agents are streamlining automation, but public skill registries are creating new security vulnerabilities.

New research reveals that the geometry of global production networks is creating a permanently fragile system increasingly susceptible to cascading failures.

Researchers are applying techniques from topology to understand the stability of cryptocurrency price movements and improve risk management strategies.

A new framework proposes applying epidemiological principles to understand and measure the pervasive impact of artificial intelligence on the wellbeing of communities.

A comprehensive review reveals that combining log analysis with execution trace modeling offers the most effective approach to pinpointing and classifying faults in complex distributed systems.

New research reveals that large language models are surprisingly susceptible to numerical instability, potentially leading to unpredictable outputs and systemic failures.