StableJudge: A Lightweight Adversarial Defense Framework for LLM-as-a-Judge
Large language models (LLMs) are increasingly used as judges to assign scalar scores that drive downstream decision-making, including tasks such as paper review and recommendation. However, LLM-as-a-Judge pipelines are vulnerable to score-hijacking prompt injection embedded in evaluated content, which corrupts scoring signals and distorts induced rankings. Existing defenses often enforce robustness by modifying the judge model itself, making safety dependent on a specific model's scale and training and requiring repeated effort when the judge is updated or replaced. We propose StableJudge, a lightweight defense framework that externalizes prompt-injection mitigation as a reusable pre-scor...
| Authors | Anning Hu, Yangyu Li, Yuqi Huang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 12 October 2026 |
| Last updated at source | 12 October 2026 |
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