Language Model

Artificial intelligence technology is making strides in the field of multimodal large language models (MLLMs), which combine verbal and visual comprehension to create precise representations of multimodal inputs. Researchers from Beihang University and Microsoft have devised an innovative approach called the E5-V framework. This framework seeks to overcome prevalent limitations in multimodal learning, including; the…

Large Language Models (LLMs) have transformed natural language processing, despite limitations such as temporal knowledge constraints, struggles with complex mathematics, and propensity for producing incorrect information. The integration of LLMs with external data and applications presents a promising solution to these challenges, improving accuracy, relevance, and computational abilities. Transformers, a pivotal development in natural language…

Large Language Models (LLMs) like ChatGPT have become widely accepted in various sectors, making it increasingly challenging to differentiate AI-generated content from human-written material. This has raised concerns in scientific research and media, where undetectable AI-generated texts can potentially introduce false information. Studies show that human ability to identify AI-generated content is barely better than…

Training Large Language Models (LLMs) has become more demanding as they require an enormous amount of data to function efficiently. This has led to increased computational expenses, making it challenging to reduce training costs without impacting their performance. Conventionally, LLMs are trained using next token prediction, predicting the next token in a sequence. However, Pattern…

Language models have undergone significant developments in recent years which has revolutionized artificial intelligence (AI). Large language models (LLMs) are responsible for the creation of language agents capable of autonomously solving complex tasks. However, the development of these agents involves challenges that limit their adaptability, robustness, and versatility. Manual task decomposition into LLM pipelines is…