Language models (LMs), while powerful in generating human-like text, often produce unstructured and inconsistent outputs. The lack of structure in responses poses challenges in real-world applications, especially in long and extensive responses. It becomes difficult to extract specific information, integrate with systems expecting structured data, and present information in formats like tables or lists that…
Quantum computing has shown great potential to transform specific algorithms and applications and is expected to work alongside traditional High-Performance Computing (HPC) environments. Moreover, Noisy Intermediate-Scale Quantum (NISQ) devices have emerged as powerful computational platforms, but they face challenges such as limited qubit coherence times and a high chance of errors. Due to the complexity…
Computational social science (CSS) leverages advanced computational techniques to analyze and interpret vast amounts of social data. This field increasingly relies on natural language processing (NLP) methods to handle unstructured text data. However, while large language models (LLMs) have revolutionized CSS by enabling rapid and sophisticated text analysis, their integration into practical applications remains a…
Building Information Modeling (BIM) is an all-encompassing method of representing built assets using geometric and semantic data. This data can be used throughout a building’s lifetime and shared in dedicated forms throughout project stakeholders. Current building information modeling (BIM) authoring software considers various design needs. Because of this unified strategy, the software now includes many…
Mental health profoundly impacts individuals’ quality of life, yet accessing mental health services can be challenging due to stigma, insufficient workforce, and fragmented care systems. NLP has demonstrated its potential in this area, with models developed to detect symptoms and evaluate depression from clinical texts. Language models like BERT have also been adapted for classifying…
Professionals and enthusiasts in the finance industry need to have dependable tools for accessing and analyzing large amounts of data in order to track macroeconomic trends, cryptocurrency, equities markets, and forex. A comprehensive platform that gathers all this data in one location is essential. Many existing platforms are expensive or restrict data access and user…
The year 2023 witnessed a rapid rise in generative AI, which has led to the development of numerous AI applications designed to tackle various tasks. Despite their power, these tools often face a significant challenge: integration into daily life. Implementing AI into daily routines can be challenging, making it less effective despite its potential. Meet…
Dense Retrieval (DR) models are an advanced method in information retrieval (IR) that uses deep learning techniques to map passages and queries into an embedding space. The model can determine the semantic relationships between them by comparing the embeddings of the query and the passages using this embedding space. DR models seek to strike a…