constrainedtext

Constrainedtext is a term used in natural language processing to describe text produced under predefined constraints. It covers generation and editing tasks where outputs must satisfy requirements such as including specific keywords, following a given syntactic structure, matching a target tone, or staying within a fixed length. Constraints can be lexical, syntactic, stylistic, topical, or safety-related, and may be hard (guaranteed) or soft (penalized rather than strictly enforced).

In practice, constrained text generation is implemented with specialized decoding or editing techniques that steer a language model toward the constraint set. Common approaches include lexical-constrained decoding, where required tokens must appear in the output; grammar-based or automaton-guided methods that enforce structural constraints; and post-editing or prompt-engineering strategies that bias the result toward the constraints. More flexible systems combine a base language model with constraints via penalties, plug-and-play methods, or constrained beam search.

Applications span content creation, translation, summarization, accessibility, and interactive storytelling. For example, marketing copy might need to include brand terms; educational material may require the use of domain terminology; and safety or policy constraints may forbid certain words or topics.

Challenges include maintaining fluency and coherence while satisfying multiple constraints, measuring constraint satisfaction, and managing the computational cost of constrained decoding. Ongoing work seeks to integrate richer constraint representations, improve evaluation, and scale to long-form text. Related concepts include constrained natural language generation and lexically constrained decoding.