2 papers
cs.LG2025
Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation
Ryotaro Shimizu, Takashi Wada, Yu Wang +9
Recent research on explainable recommendation generally frames the task as a standard text generation problem, and evaluates models simply based on the textual similarity between t…
cs.CV2024
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model
Kosuke Sakurai, Tatsuya Ishii, Ryotaro Shimizu +2
In recent years, considerable research has been conducted on vision-language models that handle both image and text data; these models are being applied to diverse downstream tasks…