Unverified50% confidenceFactExact time
Constrained decoding dynamically filters the vocabulary through external logic at each token generation step, allowing only grammatically valid tokens to be sampled; common implementations include Outlines, LMQL, and the json_schema response format built into inference engines.
1
Sources
50%
Confidence
Long-term
Relevance
10/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedStructured output applies constraints to the model's token sampling via constrained decoding, typically based on finite-state automata (FSA) or context-free grammars (CFG).75% similarUnverifiedToken control is typically implemented through system prompt injection rules, output filter regex matching, or RLHF fine-tuning.74% similarUnverifiedGBNF 通过在每个 Token 生成步骤对 logits 进行掩码过滤，强制模型只能生成符合预定义语法规则的 Token 序列72% similarUnverifiedConstrained decoding allows only tokens conforming to grammar rules to be sampled by setting the logits of illegal tokens to negative infinity at each decoding step; FSM is applicable to regular languages, while CFG can handle nested structures such as JSON and XML.72% similarUnverifiedConstrained Decoding guarantees at the sampling level that outputs will conform to a specified JSON Schema or regular expression; typical open-source implementations include Outlines, Guidance, and LM Format Enforcer.70% similar
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