Recent Breakthroughs in Natural Language Generation: Unveiling CuttingEdge Techniques and Diverse Applications in Modern Communication

EasyChair Preprint 11954

Abstract

The field of Natural Language Generation (NLG) has witnessed remarkable strides, marked by recent breakthroughs that have unveiled cutting-edge techniques and diversified applications, particularly in the realm of modern communication. This paper aims to provide a comprehensive overview of these advancements, shedding light on the innovative methodologies that have reshaped the landscape of NLG. In the pursuit of more fluent and contextually aware language generation, researchers have delved into neural language models, leveraging deep learning architectures to enhance the coherence and naturalness of generated text. Transformer-based models, such as GPT-3, have emerged as pivotal tools in NLG, showcasing unparalleled capabilities in understanding and generating human-like language across various domains. Furthermore, this paper explores the practical applications of these breakthroughs, emphasizing their impact on diverse sectors. From content creation and marketing to virtual assistants and automated customer support, NLG has found its way into numerous facets of modern communication. The synergy of advanced NLG techniques with real-world applications has not only streamlined content generation processes but has also elevated the overall quality of automated communication, fostering more engaging and personalized interactions

Keyphrases: NLG, Natural Language Generation, Neural Language Models, breakthroughs, cutting-edge techniques, deep learning, modern communication

@booklet{EasyChair:11954,
  author    = {William Jack and Muss Eligibly},
  title     = {Recent Breakthroughs in Natural Language Generation: Unveiling CuttingEdge Techniques and Diverse Applications in Modern Communication},
  howpublished = {EasyChair Preprint 11954},
  year      = {EasyChair, 2024}}