Token Masking And Sampling Integration

Structured text generation — guarantees LLM outputs match JSON schemas or grammars.

Unique: Integrates masking directly into the sampling pipeline by zeroing invalid tokens in the logits before applying temperature and sampling strategies, preserving the model's probabilistic behavior while enforcing constraints.

vs others: Maintains sampling diversity (vs. greedy decoding) while guaranteeing constraint compliance; more efficient than rejection sampling because invalid tokens are never sampled.