Refusal-Gated Decoding: Preserving Refusal Behavior Under High-Temperature Sampling
Factual evidence
What the source reports
Researchers propose "Refusal-Gated Decoding" to maintain LLM refusal behaviors when using high-temperature sampling for output diversity.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 7 October 2026
- Collected by OneBench
- 24 Jul 2026, 09:51 UK
Stored source excerpt
arXiv:2607.20791v1 Announce Type: cross Abstract: High-temperature sampling is one of the primary mechanisms for increasing diversity in LLMs. Recent advances in truncation-based sampling techniques have…
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OneBench interpretation
Institutional assessment
So what
Maintaining an LLM's safety alignment and refusal capabilities while enabling diverse outputs for user experience is a critical challenge for enterprise deployment.
Do what
This research provides a technical pathway to address the tension between model safety and output diversity, impacting the usability and risk profile of production LLMs.