Recursive generation, evaluation, and refinement of discrete prompts tunes a black-box multimodal LLM to each user, raising personalized visual emotion recognition accuracy on Affection from 40.6% to 44.9%.
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Discrete Prompt Tuning via Recursive Utilization of Black-box Multimodal Large Language Model for Personalized Visual Emotion Recognition
Recursive generation, evaluation, and refinement of discrete prompts tunes a black-box multimodal LLM to each user, raising personalized visual emotion recognition accuracy on Affection from 40.6% to 44.9%.