3 accepted papers
Federated learning is a collaborative machine learning framework where multiple clients jointly train a global model. To mitigate communication overhead, it is common to select a subset of clients for participation in each training round. However, existing client selection strategies often rely on a…
Multi-Modal Entity Alignment (MMEA) aims to identify equivalent entities across different knowledge graphs by utilizing auxiliary modalities such as images. While MMEA has made significant progress, prevailing methods still heavily rely on abundant annotated entity pairs. Active learning seeks to al…
Transferring visual language models (VLMs) from the image domain to the video domain has recently yielded great success on human action recognition tasks. However, standard recognition paradigms overlook fine-grained action parsing knowledge that could enhance the recognition accuracy. In this paper…