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Evidence record 4059 · automatically gathered

Exploring and Developing a Pre-Model Safeguard with Draft Models

Large Language Model (LLM) alignment remains vulnerable to jailbreak attacks that elicit unsafe responses, motivating pre-model and post-model guards. Pre-model guards audit the safety of prompts before invoking target models. However, relying solely on the prompt often leads to high false-negative rates (i.e., jailbreak attacks go undetected). Post-model guards address this issue by auditing both the user prompt and the target model's response. However, they incur a high computational cost, inc

Record details

Published: 19 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Safety & alignment · Shared topic: Transparency

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Shared topic: Safety & alignment · Shared topic: Transparency

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Shared topic: Safety & alignment · Shared topic: Transparency

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Shared topic: Safety & alignment · Shared topic: Transparency

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Shared topic: Safety & alignment · Shared topic: Transparency

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How to cite this record

ethics.ai (19 May 2026), “Exploring and Developing a Pre-Model Safeguard with Draft Models,” evidence record 4059, https://ethics.ai/record/4059 (originally published by arXiv).

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