CLAIFeb 25, 2024

From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility

arXiv:2402.16142v181 citationsh-index: 12
Originality Synthesis-oriented
AI Analysis

It addresses the need for a comprehensive analysis of LLMs' impact beyond traditional NLP, highlighting untapped opportunities for researchers and practitioners in various fields.

This review paper systematically examines the versatility of Large Language Models (LLMs) like GPT and BERT across diverse domains, identifying research gaps and potential applications in areas such as fitness, urban planning, and disaster management.

This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from technology, finance, healthcare to education. Despite their established prowess in Natural Language Processing (NLP), these LLMs have not been systematically examined for their impact on domains such as fitness, and holistic well-being, urban planning, climate modelling as well as disaster management. This review paper, in addition to furnishing a comprehensive analysis of the vast expanse and extent of LLMs' utility in diverse domains, recognizes the research gaps and realms where the potential of LLMs is yet to be harnessed. This study uncovers innovative ways in which LLMs can leave a mark in the fields like fitness and wellbeing, urban planning, climate modelling and disaster response which could inspire future researches and applications in the said avenues.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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