Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2
  Model
Rohit Pandey Hetvi Waghela Sneha Rakshit Aparna Rangari Anjali Singh Rahul Kumar Ratnadeep Ghosal Jaydip Sen
This work delved into the realm of automatic text generation, exploring a
variety of techniques ranging from traditional deterministic approaches to more
modern stochastic methods. Through analysis of greedy search, beam search,
top-k sampling, top-p sampling, contrastive searching, and locally typical
searching, this work has provided valuable insights into the strengths,
weaknesses, and potential applications of each method. Each text-generating
method is evaluated using several standard metrics and a comparative study has
been made on the performance of the approaches. Finally, some future directions
of research in the field of automatic text generation are also identified.