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: The paper demonstrates that by effectively fine-tuning or prompting CLIP, models can achieve significantly higher accuracy in recognizing verbs and their associated semantic roles compared to previous state-of-the-art systems.

: They introduce methods to adapt CLIP's powerful visual-linguistic representations specifically for the task of generating structured descriptions that capture the "who, what, and where" of a scene. 1ffc83b3aa8c274a2477daf6aff5dad7_origi.jpg

: The researchers address the limitations of existing situational recognition models by leveraging the CLIP (Contrastive Language-Image Pre-training) framework to improve how machines describe complex human-object interactions. : The paper demonstrates that by effectively fine-tuning