6 accepted papers
Coupled spatiotemporal forecasting is important for predicting the future evolution of multiple interacting dynamical systems, such as in climate models. However, existing methods are severely constrained by the persistent bottleneck of compounding errors. In coupled systems, errors from each subsys…
Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to a reactive paradigm, where they merely execute explicit user commands. The emerging paradigm of proactive intelligence, where agents autonomously
The core of Multi-View Stereo (MVS) is to find corresponding pixels in neighboring images. However, due to challenging regions in input images such as untextured areas, repetitive patterns, or reflective surfaces, existing methods struggle to find precise pixel correspondence therein, resulting in i
Upper limb amputees face significant challenges in their daily lives due to the loss of hand or arm functionality. Researchers have developed upper limb prostheses to restore normal hand movements for them. Most hand movement recognition systems of prostheses use electromyography (EMG) as the input…
Stereo matching methods based on iterative optimization like RAFT-Stereo and IGEV-Stereo have evolved into a cornerstone in the field of stereo matching. However these methods struggle to simultaneously capture high-frequency information in edges and low-frequency information in smooth regions due t…
In Neural Machine Translation (NMT), data augmentation methods such as back-translation have proven their effectiveness in improving translation performance. In this paper, we propose a novel data augmentation approach for NMT, which is independent of any additional training data. Our approach, AdMi…