3 papers
cs.LG2024
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…
cs.CV2023
SCP: Spherical-Coordinate-based Learned Point Cloud Compression
Ao Luo, Linxin Song, Keisuke Nonaka +4
In recent years, the task of learned point cloud compression has gained prominence. An important type of point cloud, the spinning LiDAR point cloud, is generated by spinning LiDAR…