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Conversational Voice, a pipeline that converts real two-speaker excerpts into three complementary training-data artifacts, is presented, a pipeline that converts real two-speaker excerpts into three complementary training-data artifacts.
Unfaithful reasoning chains can significantly undermine the accuracy of MLLMs, but a training-free framework can effectively correct these errors and boost performance by over 8%.
