Constrained decoding does not inherently degrade LLM reasoning, contrary to common assumption

Authors show apparent performance drops stem from prompt mismatches, while validity constraints reliably improve accuracy.

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Ngoc Trinh Hung Nguyen · Alonso Silva · Armen Aghasaryan · Mehwish Alam

Télécom Paris · Nokia Bell Labs

Research Digest··2 min read
Illustration: Constrained decoding does not inherently degrade LLM reasoning, contrary to common assumption
The authors revisit the assumption that constrained decoding inherently harms LLM reasoning.

The authors separate constrained decoding into three constraint types: format constraints (FC), which enforce output structure such as JSON; validity constraints (VC), which mask continuations that violate task-level requirements like data type or length; and reasoning constraints (RC), which restrict the model's reasoning trajectory.

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