Oleg Zendel

The Effect of Multi-Lingual and Keyword Adversarial Injection on LLM Relevance Judgment

This work investigates the impact of cross-lingual prompt injection attacks on LLM-based relevance judgments using TREC Deep Learning collections and two open-weight models under established prompting frameworks, and demonstrates that multilingual query-based injections are highly effective in inflating relevance scores while simultaneously evading existing prompt-injection defenses.