3 accepted papers
Label Distribution Learning (LDL) is a groundbreaking paradigm for addressing the task with label ambiguity. Subjectivity in annotating label description degrees often leads to imbalanced label distribution. Existing approaches either adopt representation alignment or decoupling strategies to solve
Conditional molecular generation, aiming to generate 2D and 3D molecules that satisfy given properties, has achieved remarkable progress, thanks to the advances in deep generative models such as graph diffusion. However, existing methods generally assume that the given conditions for training and te
Ranking aggregation (RA), the process of aggregating multiple rankings derived from multiple search strategies, has been proved effective in person re-identification (re-ID) because of a single re-ID method can not always achieve consistent superiority for different scenarios. Existing RA research m…