The field of natural language processing (NLP) has seen a groundbreaking advancement with the development of MORCELA—Magnitude-Optimized Regression for Controlling Effects on Linguistic Acceptability. This innovative approach addresses the long-standing challenge of aligning language model (LM)
In the complex world of banking, fraud prevention remains an ever-evolving challenge for financial institutions. Traditional fraud detection methods, often relying on static, rule-based systems, struggle to keep pace with increasingly sophisticated fraud tactics. In this landscape, machine learning
Singapore's economy has demonstrated remarkable resilience and impressive growth throughout 2024, surpassing initial expectations and prompting an optimistic upward revision of the country's growth forecast. While the outlook for the remainder of 2024 appears strong, the nation is now turning its
Natural language processing (NLP) has made significant strides in recent years, yet aligning language model (LM) outputs with human acceptability judgments remains a challenge. A novel approach named MORCELA, developed by research teams from New York University (NYU) and Carnegie Mellon University
Artificial intelligence (AI) is revolutionizing the way businesses approach predictive analytics and market forecasting. By leveraging advanced machine learning (ML) and deep learning (DL) techniques, AI is enabling companies to make more accurate predictions, stay ahead of market trends, and make
Natural Language Processing (NLP) is revolutionizing the finance sector by leveraging linguistic and computational techniques to interpret and understand human language. This technology is instrumental in extracting insights from unstructured data such as news articles, financial reports, and
