ObfusQAte: A Proposed Framework to Evaluate LLM Robustness on Obfuscated Factual Question Answering

Researchers introduce ObfusQAte, a new framework to test Large Language Model robustness when faced with obfuscated or disguised factual questions. The study reveals that LLMs tend to fail or generate hallucinated responses when confronted with increasingly complex variations of questions across three dimensions of obfuscation.