7 accepted papers
Model predictive control (MPC) faces significant limitations when applied to systems evolving on nonlinear manifolds, such as robotic attitude dynamics and constrained motion planning, where traditional Euclidean formulations struggle with singularities, over-parameterization, and poor convergence. …
Recently, significant progress has been made in protein-ligand docking, especially in deep learning methods, and some benchmarks were proposed, such as PoseBench and PLINDER. However, these studies typically focus on the self-docking scenario, which is less practical in real-world applications. More…
Large language models (LLMs) have shown superb capability of modeling multimodal signals including audio and text, allowing the model to generate spoken or textual response given a speech input. However, it remains a challenge for the model to recognize personal named entities, such as contacts in a…
Automatic dysarthric speech recognition (ADSR) remains challenging due to the irregularities in speech caused by motor control impairments and the limited availability of dysarthric speech data. This paper explores the integration of articulatory features, captured using Electromagnetic Articulograp…
The prevalent issue in urban trajectory data usage, notably in low-sample rate datasets, revolves around the accuracy of travel time estimations, traffic flow predictions, and trajectory similarity measurements. Conventional methods, often relying on simplistic mixes of static road networks and raw…
Variable stiffness mechanisms provide an effective means to enhance the load-bearing capacity of soft fingers, but due to the lack of stretchability, their assembly position is often limited to the lower surface of soft bending actuators. Here, a Cross-Sliding jamming mechanism with tensile properti
In recent years, neural image compression emerges as a rapidly developing topic in computer vision, where the state-of-the-art approaches now exhibit superior compression performance than their conventional counterparts. Despite the great progress, current methods still have limitations in preservin…