Better GPT

Research on "better GPT" focuses on improving the capabilities and reliability of large language models (LLMs) like GPT, primarily through techniques like retrieval-augmented pretraining and instruction tuning. Current efforts concentrate on enhancing factual accuracy, mitigating biases (such as over-scoring AI-generated text), and improving the efficiency of data extraction from scientific literature using LLMs. These advancements have significant implications for various fields, including scientific data management, automated fact-checking, and the creation of educational resources, by enabling more efficient and accurate information processing and knowledge synthesis.