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.
New research demonstrates how probabilistic reconstruction techniques can reliably identify performance issues in residential solar thermal installations.
A new study reveals that standard NLP evaluation metrics struggle to accurately assess semantic similarity in financial text where numerical values play a critical role.
Researchers are using AI-powered agents to model the complex dynamics of misinformation as it travels through social networks.
Researchers are exploring a novel approach to AI by focusing on the dynamic processes of neuronal input and output, aiming to replicate the core mechanisms of human intelligence.
A new framework, TermGPT, aims to bridge the gap between general language understanding and the nuanced vocabulary of fields like law and finance.
Researchers are developing new methods to classify disaster events from social media data that account for inherent biases and improve prediction accuracy for previously unseen crises.
A new approach leverages historical macroeconomic patterns to improve the robustness and accuracy of financial predictions, especially during periods of market instability.
Researchers have developed a novel deep learning framework that leverages the complex interplay of fractal patterns and chaotic dynamics to improve the accuracy of financial volatility predictions.