CoConflictQA is a benchmark designed to evaluate the contextual faithfulness of Large Language Models (LLMs) by focusing on their tendency to hallucinate during question answering. It aims to provide a more reliable assessment of how well LLMs align their responses with the given context.

This dataset is constructed based on six widely-used QA datasets:

• HotpotQA
• NewsQA
• Natural Questions (NQ)
• SearchQA
• SQuAD
• TriviaQA

CoConflictQA was introduced in the paper: PIP-KAG: Mitigating Knowledge Conflicts in Knowledge-Augmented Generation via Parametric Pruning