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Unified multimodal models may excel in generation and understanding, but they often falter when reasoning about their own outputs, revealing hidden weaknesses in their capabilities.
Ditch imperfect human annotations: this dual-reward RL approach trains image captioning models to be both more complete and more factually correct.
