Edit Distance

Edit distance quantifies the difference between two sequences, such as strings of text or genetic sequences, by counting the minimum number of edits (insertions, deletions, substitutions) needed to transform one into the other. Current research focuses on improving the efficiency and robustness of edit distance calculations, particularly within the context of natural language processing tasks like detecting AI-generated text, correcting speech recognition errors, and enhancing machine learning models. These advancements have significant implications for various fields, including combating misinformation, improving human-computer interaction, and optimizing machine learning training processes.