5 accepted papers
Federated learning (FL) has emerged as a distributed machine learning paradigm due to its privacy-preserving advantages. Most FL studies assume offline labeled datasets are available at clients. In practice, however, client data often arrive without labels in a streaming manner, making label acquisi
Camouflaged object detection (COD) aims to segment objects that visually blend into their surroundings. However, the subtle differences between camouflaged objects and the background make this task highly challenging. Therefore, how to represent and learn local details and global contexts is crucial…
The ability to accurately interpret complex visual information is a crucial topic of multimodal large language models (MLLMs). Recent work indicates that enhanced visual perception significantly reduces hallucinations and improves performance on resolution-sensitive tasks, such as optical character…
Humor is previously regarded as a gift exclusive to humans for the following reasons. Humor is a culturally nuanced aspect of human language, presenting challenges for its understanding and generation. Humor generation necessitates a multi-hop reasoning process, with each hop founded on proper ratio…
As a broad and major category in machine reading comprehension (MRC), the generalized goal of discriminative MRC is answer prediction from the given materials. However, the focuses of various discriminative MRC tasks may be diverse enough: multi-choice MRC requires model to highlight and integrate a…