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Mitigating Dialogue Hallucination for Large Multi-modal Models via Adversarial Instruction Tuning
To precisely measure this, we first present an evaluation benchmark by extending popular multi-modal benchmark datasets with prepended hallucinatory dialogues generated by our novel Adversarial Question Generator, which can automatically generate image-related yet adversarial dialogues by adopting adversarial attacks on LMMs.
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