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Metaphor explanations are not just about quality; they reveal a complex, multidimensional landscape that challenges traditional evaluation methods.
Trajectories computed through this method are not only efficient but also traceable to their underlying models, offering a level of interpretability that traditional learning methods lack.
By integrating commonsense reasoning into scene graph generation, this framework achieves consistent performance boosts, even in sparsely annotated scenarios.