Large Language Model

Large Language Models (LLMs) have revolutionized natural language processing tasks, and their potential in physical world planning tasks is beginning to be leveraged. However, these models often encounter problems in understanding the actual world, resulting in hallucinatory actions and a reliance on trial-and-error behavior. Researchers have noted that humans perform tasks efficiently by leveraging global…

The rapid advancement of large language models (LLMs) has paved the way for the development of numerous Natural Language Processing (NLP) applications, including chatbots, writing assistants, and programming tools. However, these applications often necessitate infinite input lengths and robust memory capabilities, features currently lacking in existing LLMs. Preserving memory and accommodating infinite input lengths remain…

Machine Translation (MT), part of Natural Language Processing (NLP), aims to automate the translation of text from one language to another using large language models (LLMs). The goal is to improve translation accuracy for better global communication and information exchange. The challenge in improving MT is using high-quality, diverse training data for instruction fine-tuning, which…

Artificial intelligence (AI) has reshaped multiple industries, including finance, where it has automated tasks and enhanced accuracy and efficiency. Yet, a gap still exists between the finance sector and AI community due to proprietary financial data and the specialized knowledge required to analyze it. Therefore, more advanced AI tools are required to democratize the use…