arXiv · 2404.01786
Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2 Model
Abstract
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.
Explore related subjects
Keep this discovery
Rohit Pandey, Hetvi Waghela, Sneha Rakshit, Aparna Rangari, Anjali Singh, Rahul Kumar, Ratnadeep Ghosal, Jaydip Sen. 2024-04-02. Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2 Model. https://arxiv.org/abs/2404.01786
Cite the original work for its findings. Save a collection to share your selection of sources.