P-MLLM augments a frozen LLM with selective fusion modules to incorporate visual information in a profile-conditioned manner for competitive zero-shot PIAA performance.
We follow the evaluation protocol of PARA [1], with mi- nor modifications to the data construction
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Enhancing Zero-shot Personalized Image Aesthetics Assessment with Profile-aware Multimodal LLM
P-MLLM augments a frozen LLM with selective fusion modules to incorporate visual information in a profile-conditioned manner for competitive zero-shot PIAA performance.