8 accepted papers
Despite the progress in quantum computing, one major bottleneck against the practical utility is its susceptibility to noise, which frequently occurs in current quantum systems. Existing quantum error mitigation (QEM) methods either lack generality to noise and circuit types or fail to capture the g…
This paper presents CoCube a tabletop modular robotics platform designed for robotics education and multirobot algorithm research. CoCube is characterized by its low cost low floors high ceilings and wide walls offering flexibility and broad applicability across various use cases. The platform compr
Despite their proficiency in general tasks, Multi-modal Large Language Models (MLLMs) struggle with automatic Geometry Problem Solving (GPS), which demands understanding diagrams, interpreting symbols, and performing complex reasoning. This limitation arises from their pre-training on natural images…
Spiking Neural Networks (SNNs) have demonstrated remarkable potential across many domains, including computer vision and natural language processing, owing to their energy efficiency and biological plausibility. However, their application in long-term prediction tasks remains underexplored, which is…
Audio- and Video-Driven Talking Head Generation methods have attracted considerable research interest due to recent advances in Artificial Intelligence Generated Content (AIGC) technologies. In such approaches, a single image is artificially animated by leveraging audio and/or motion features extrac…
This study presents a novel multi-branch hybrid network framework based on structural re-parameterization for underwater small object detection, referred to as SRP-UOD. The developed framework employs multi-branch convolutions with ReBottleneck-ResNets, which are re-parameterized based on structural…
Automatic quantum architecture search (QAS) has been widely studied across disciplines with different implications. In this paper, beyond a particular domain, we formulate the QAS problem into two basic (and relatively even ideal) tasks: i) arbitrary quantum circuit (QC) regeneration given a target…
With the arrival of the Noisy Intermediate-Scale Quantum (NISQ) era and the fast development of machine learning, variational quantum algorithms (VQA) including Variational Quantum Eigensolver (VQE) and quantum neural network (QNN) have received increasing attention with wide potential applications…