Brill's Tagger as an Early Example of Predict-then-Refine

Modern NLP Applications of the Predict-then-Refine Paradigm

Self-Refinement in LLMs

An AI-powered code completion tool is designed to help developers write functions. When a developer provides a function name and a comment describing its purpose, the tool first generates a complete, functional block of code. Following this initial generation, the tool enters a loop where it analyzes the code it just wrote, identifies potential inefficiencies or non-standard practices, and applies a specific correction. This analysis-and-correction loop repeats several times, with the code block

Distinguishing NLP System Architectures

Analyzing System Architectures for Output Generation

Sequential Scaling