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arXiv:2601.20511v1 Announce Type: new Abstract: As social media platforms proliferate, users increasingly demand intuitive ways to create diverse, high-quality portrait collections. In this work, we...
arXiv:2601.20518v1 Announce Type: new Abstract: Topological deep learning has emerged for modeling higher-order relational structures beyond pairwise interactions that standard graph neural networks fail to...
arXiv:2601.20520v1 Announce Type: new Abstract: Recent diffusion-based Multimodal Large Language Models (dMLLMs) suffer from high inference latency and therefore rely on caching techniques to accelerate...
arXiv:2601.20524v1 Announce Type: new Abstract: Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images....
arXiv:2601.20526v1 Announce Type: new Abstract: Recently, adapting pre-trained models to downstream tasks has attracted increasing interest. Previous Parameter-Efficient-Tuning (PET) methods regard the pre-trained model as...
arXiv:2601.20529v1 Announce Type: new Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration...
arXiv:2601.20537v1 Announce Type: new Abstract: Markov-modulated fluid queues (MMFQs) are a powerful modeling framework for analyzing the performance of computer and communication systems. Their distinguishing...
arXiv:2601.20538v1 Announce Type: new Abstract: Large language model-powered multi-agent systems have emerged as powerful tools for simulating complex human-like systems. The interactions within these systems...
arXiv:2601.20539v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled automated heuristic design (AHD) for combinatorial optimization problems (COPs), but existing frameworks' reliance on...
arXiv:2601.20544v1 Announce Type: new Abstract: Data Visualization Literacy assessments are typically administered via fixed sets of Data Visualization items, despite substantial heterogeneity in how different...
arXiv:2601.20546v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in verbal creative tasks. However, previous assessments of the creative capabilities of LLMs...
arXiv:2601.20548v1 Announce Type: new Abstract: This paper critically examines the device identification process using machine learning, addressing common pitfalls in existing literature. We analyze the...
arXiv:2601.20552v1 Announce Type: new Abstract: We present DeepSeek-OCR 2 to investigate the feasibility of a novel encoder-DeepEncoder V2-capable of dynamically reordering visual tokens upon image...
arXiv:2601.20554v1 Announce Type: new Abstract: We study risk-sensitive planning under partial observability using the dynamic risk measure Iterated Conditional Value-at-Risk (ICVaR). A policy evaluation algorithm...
arXiv:2601.20555v1 Announce Type: new Abstract: Rich contact perception is crucial for robotic manipulation, yet traditional tactile skins remain expensive and complex to integrate. This paper...
arXiv:2601.20556v1 Announce Type: new Abstract: Unsupervised ensemble learning emerged to address the challenge of combining multiple learners' predictions without access to ground truth labels or...
arXiv:2601.20561v1 Announce Type: new Abstract: Transmission electron microscopes (TEMs) enable atomic-scale imaging but suffer from aberrations caused by lens imperfections and environmental conditions, reducing image...
arXiv:2601.20564v1 Announce Type: new Abstract: The practical deployment of diffusion-based Neural Video Compression (NVC) faces critical challenges, including severe information loss, prohibitive inference latency, and...
arXiv:2601.20566v1 Announce Type: new Abstract: This paper investigates the time fractional sine-Gordon equation whose solution exhibits a weak singularity of type t^{\alpha}. By means of...
arXiv:2601.20568v1 Announce Type: new Abstract: During pretraining, LLMs inadvertently memorize sensitive or copyrighted data, posing significant compliance challenges under legal frameworks like the GDPR and...
arXiv:2601.20571v1 Announce Type: new Abstract: Specifications for decentralized learning on resource-constrained edge devices require algorithms that are communication-efficient, robust to data corruption, and lightweight in...
arXiv:2601.20573v1 Announce Type: new Abstract: Speech emotion recognition (SER) is crucial in speech understanding and generation. Most approaches are based on either classification models or...
arXiv:2601.20577v1 Announce Type: new Abstract: Multi-robot systems have been widely deployed in real-world applications, providing significant improvements in efficiency and reductions in labor costs. However,...
arXiv:2601.20578v1 Announce Type: new Abstract: Who benefits from expanding transport networks? While designed to improve mobility, such interventions can also create inequality. In this paper,...