Lexical Constraint

Lexical constraint in natural language processing focuses on controlling the generation of text to include or exclude specific words or phrases, improving the accuracy and relevance of outputs in various applications. Current research investigates methods for effectively incorporating these constraints into large language models (LLMs), often employing techniques like divide-and-conquer strategies, attention mechanisms that integrate vectorized constraints, and modified decoding algorithms to address challenges such as position bias and handling low-frequency words. This work is significant for enhancing the controllability and reliability of LLMs in tasks ranging from machine translation and text summarization to generating explanations for recommendations and creating specialized lexicons for diverse audiences.