6 accepted papers
Tracking moving anatomical targets with robotic ultrasound is particularly challenging when the target motion is both fast and large in scale, as the end-to-end latency of existing systems prevents the perception–control loop from closing fast enough. In this paper, we argue that overcoming this lim…
Dereverberation has long been a crucial research topic in speech processing, aiming to alleviate the adverse effects of reverberation in voice communication and speech interaction systems. Among existing approaches, forward convolutional prediction (FCP) has recently attracted attention. It typicall…
Contact dynamics critically influence the sim-to-real performance of deformable tissue retraction—a representative contact-rich manipulation task in robotic surgery. The uncertainty in instrument-tissue interactions further complicates its automation. To address these challenges, we propose an archi
State space models (SSMs), particularly Mamba, have shown promise in NLP tasks and are increasingly applied to vision tasks. However, most Mamba-based vision models focus on network architecture and scan paths, with little attention to the SSM module. In order to explore the potential of SSMs, we mo…
Pre-trained language models (PLMs) are increasingly being applied to code-related tasks. Although PLMs have achieved good results, they do not take into account potential high-order data correlations within the code. We propose three types of high-order correlations in code tokens, i.e. abstract syn
In reinforcement learning with sparse rewards, demonstrations can accelerate learning, but determining when to imitate them remains challenging. We propose Smooth Policy Regularisation from Demonstrations (SPReD), a framework that addresses the fundamental question: when should an agent imitate a de…