constrained generation

**Constrained generation** is the **text generation under explicit lexical, structural, or semantic restrictions that limit valid outputs** - it is used when correctness and format requirements outweigh free-form creativity. **What Is Constrained generation?** - **Definition**: Decoding framework that permits only outputs satisfying specified constraints. - **Constraint Types**: Lexicon allowlists, grammar rules, schema requirements, and policy filters. - **Runtime Techniques**: Logit masking, guided search, grammar engines, and verifier-in-the-loop. - **Product Context**: Common in assistants that output code, JSON, or regulated language. **Why Constrained generation Matters** - **Reliability**: Reduces malformed outputs and protocol-breaking responses. - **Safety**: Constrains harmful or out-of-policy token paths. - **Automation Readiness**: Structured constraints make outputs easier for machine execution. - **Compliance**: Supports legal and operational language requirements. - **Debuggability**: Narrowed output space simplifies failure analysis. **How It Is Used in Practice** - **Constraint Modeling**: Express requirements in machine-checkable grammar or schema rules. - **Incremental Validation**: Check partial outputs during decoding, not only at completion. - **Performance Tuning**: Measure latency impact of constraints and optimize pruning logic. Constrained generation is **a core strategy for dependable machine-consumable LLM output** - strong constraints improve safety and integration quality at scale.