Multimodal fusion focuses on integrating information from multiple modalities with the goal of
more accurate prediction, which has achieved remarkable progress in a wide range of …

To overcome the imbalanced multimodal learning problem, where models prefer the training
of specific modalities, existing methods propose to control the training of uni-modal …

Multimodal learning methods with targeted unimodal learning objectives have exhibited
their superior efficacy in alleviating the imbalanced multimodal learning problem. However …

Humans possess a remarkable talent for flexibly alternating to different senses when
interacting with the environment. Picture a chef skillfully gauging the timing of ingredient …

Multimodal learning is expected to boost model performance by integrating information from
different modalities. However, its potential is not fully exploited because the widely-used …

Knowledge distillation (KD) has proven highly effective for compressing large models and
enhancing the performance of smaller ones. However, its effectiveness diminishes in cross …