Large Language Model

Information extraction (IE) is a crucial aspect of artificial intelligence, which involves transforming unstructured text into structured and actionable data. Traditional large language models (LLMs), while having high capacities, often struggle to properly comprehend and perform detailed specific directives necessary for effective IE. This problem is particularly evident in closed IE tasks that require adherence…

Structured commonsense reasoning in natural language processing (NLP) is a vital research area focusing on enabling machines to understand and reason about everyday scenarios like humans. It involves translating natural language into interlinked concepts that mirror human logical reasoning. However, it's consistently challenging to automate and accurately model commonsense reasoning. Traditional methodologies often require robust mechanisms…

Researchers from Imperial College London and Dell have developed a new framework for transferring styles to images using text prompts to guide the process while maintaining the substance of the original image. This advanced model, called StyleMamba, addresses the computational requirements and training inefficiencies present in current text-guided stylization techniques. Traditionally, text-driven stylization requires significant computational…

Multimodal large language models (MLLMs) represent an advanced fusion of computer vision and language processing. These models have evolved from predecessors, which could only handle either text or images, to now being capable of tasks that require integrated handling of both. Despite these evolution, a highly complex issue known as 'hallucination' impairs their abilities. 'Hallucination'…

Language modeling, a key aspect of machine learning, aims to predict the likelihood of a sequence of words. Used in applications such as text summarization, translation, and auto-completion systems, it greatly improves the ability of machines to understand and generate human language. However, processing and storing large data sequences can present significant computational and memory…

Language models (LMs) are becoming increasingly important in the field of software engineering. They serve as a bridge between users and computers, improving code generated by LMs based on feedback from the machines. LMs have made significant strides in functioning independently in computer environments, which could potentially fast-track the software development process. However, the practical…

Language models play a crucial role in advancing artificial intelligence (AI) technologies, revolutionizing how machines interpret and generate text. As these models grow more intricate, they employ vast data quantities and advanced structures to improve performance and effectiveness. However, the use of such models in large scale applications is challenged by the need to balance…