Withholding the Completing Chunk: Exact Release-Boundary Equivalence for Production Streaming Guardrails
On the map: LLM safety and security → Safety alignment, refusal and guardrails
Abstract (arXiv)
Streaming language-model output creates an enforcement boundary: a control that detects a prohibited pattern after releasing its completing chunk cannot recall it. We study a production policy in which each ordered family is the conjunction of two regular-language predicates. Incremental matching is classical. The problem is exact composition at release time across arbitrary chunk partitions, including end-of-prefix word boundaries that can change on extension. We define an ASCII-explicit policy grammar, compile each predicate to a persistent nondeterministic finite automaton (NFA), distinguish stable from provisional assertion state, apply document-order family priority, and check the decision before releasing each chunk. We show that the resulting monitor is release-boundary equivalent to an absorbing cumulative oracle for every policy in the declared grammar. Production Python and TypeScript implementations were evaluated on 101,653 partitioned cases; a public surrogate added 100,345 cases. Both campaigns produced zero oracle, cross-runtime, or intended-family mismatches. In a frozen neutral-output profile, the memoized incremental and native-regex cumulative slopes at 64-character chunks were 0.973 and 1.976. At 16,384 characters the incremental median was 30.2 ms versus 96.6 ms for native cumulative scanning at that chunk size. Native regex remained faster at 512-character chunks (12.4 versus 29.4 ms), exposing the constant-factor crossover rather than hiding it. A shared per-stream cache cap and 129-symbol alphabet bound optimization state; the campaign peaked at 364 of 4,096 without bypass. The result is policy conformance for a deterministic backstop, not evidence of semantic safety or policy completeness.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Safety alignment, refusal and guardrails, one of 12 directions in LLM safety and security. Builds on 6 of its 17 references that are in the map. First posted on arXiv 10 Aug 2026.
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6 of 17 references.
Closest ancestors · 4
Same direction, newest first
- 2026SentGuard: Sentence-Level Streaming Guardrails for Large Language Models1 Jun
- 2026LLM Safety From Within: Detecting Harmful Content with Internal Representations20 Apr
- 2026Predict, Don't React: Value-Based Safety Forecasting for LLM Streaming5 Apr
- 2025Qwen3Guard Technical Report16 Oct
Other references · 2
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