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Large Language Model (LLM) agents are seeing a vast number of applications across various sectors including customer service, coding, and robotics. However, as their usage expands, the need for their adaptability to align with diverse consumer specifications has risen. The main challenge is to develop LLM agents that can successfully adopt specific personalities, enabling them…

With advancements in model architectures and training methods, Large Language Models (LLMs) such as OpenAI's GPT-3 have showcased impressive capabilities in handling complex question-answering tasks. However, these complex responses can also lead to hallucinations, where the model generates plausible but incorrect information. This is also compounded by the fact that these LLMs generate responses word-by-word,…

Large Language Models (LLMs) have transformed natural language processing, demonstrating impressive performance across an assortment of tasks. The Scaling Law suggests that increased model size enhances LLMs' capability to comprehend context and handle long sequences. Applications such as document summarization, code generation, and conversational AI leverage these properties. However, the increased cost and efficiency associated…