  Social media advertisements are key for brand marketing, aiming to attract
consumers with captivating captions and pictures or logos. While previous
research has focused on generating captions for general images, incorporating
brand personalities into social media captioning remains unexplored. Brand
personalities are shown to be affecting consumers' behaviours and social
interactions and thus are proven to be a key aspect of marketing strategies.
Current open-source multimodal LLMs are not directly suited for this task.
Hence, we propose a pipeline solution to assist brands in creating engaging
social media captions that align with the image and the brand personalities.
Our architecture is based on two parts: a the first part contains an image
captioning model that takes in an image that the brand wants to post online and
gives a plain English caption; b the second part takes in the generated caption
along with the target brand personality and outputs a catchy
personality-aligned social media caption. Along with brand personality, our
system also gives users the flexibility to provide hashtags, Instagram handles,
URLs, and named entities they want the caption to contain, making the captions
more semantically related to the social media handles. Comparative evaluations
against various baselines demonstrate the effectiveness of our approach, both
qualitatively and quantitatively.

Computation and Language