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arXiv:2602.09824v1 Announce Type: new Abstract: With the rapid advancement of IoT and edge computing, sensor networks have become indispensable, driving the need for large-scale sensor...
arXiv:2602.09825v1 Announce Type: new Abstract: Hallucinations in Large Vision-Language Models (LVLMs) pose significant security and reliability risks in real-world applications. Inspired by the observation that...
arXiv:2602.09826v1 Announce Type: new Abstract: Arabic Language Models (LMs) are pretrained predominately on Modern Standard Arabic (MSA) and are expected to transfer to its dialects....
arXiv:2602.09829v1 Announce Type: new Abstract: Large Language Models (LLMs) are reshaping recommender systems by leveraging extensive world knowledge and semantic reasoning to interpret user intent....
arXiv:2602.09832v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed to automatically label and analyze educational dialogue at scale, yet current pipelines lack...
arXiv:2602.09834v1 Announce Type: new Abstract: Sixth generation (6G) physical layer (PHY) is evolving beyond the legacy orthogonal frequency division multiplexing (OFDM)-based waveforms. In this paper,...
arXiv:2602.09838v1 Announce Type: new Abstract: Quantification is a fundamental component of everyday language use, yet little is known about how speakers decide whether and how...
arXiv:2602.09839v1 Announce Type: new Abstract: Existing multimodal retrieval benchmarks largely emphasize semantic matching on daily-life images and offer limited diagnostics of professional knowledge and complex...
arXiv:2602.09841v1 Announce Type: new Abstract: The convergence of AI and 6G network automation introduces new challenges in maintaining transparency, fairness, and accountability across multivendor management...
arXiv:2602.09846v1 Announce Type: new Abstract: Organisations are examining how generative AI can support their operational work and decision-making processes. This study investigates how employees in...
arXiv:2602.09849v1 Announce Type: new Abstract: Equipping embodied agents with the ability to reason about tasks, foresee physical outcomes, and generate precise actions is essential for...
arXiv:2602.09850v1 Announce Type: new Abstract: Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs), pretrained on general-domain...
arXiv:2602.09851v1 Announce Type: new Abstract: Feature Engineering (FE) is pivotal in automated machine learning (AutoML) but remains a bottleneck for traditional methods, which treat it...
arXiv:2602.09854v1 Announce Type: new Abstract: This paper establishes the asymptotic error distribution of the tamed Euler method for stochastic differential equations (SDEs) with a coupled...
arXiv:2602.09856v1 Announce Type: new Abstract: Autonomous GUI agents interact with environments by perceiving interfaces and executing actions. As a virtual sandbox, the GUI World model...
arXiv:2602.09857v1 Announce Type: new Abstract: Network communication using the Internet Protocol (IP) is a pillar of modern Internet applications. IP allows data packets to travel...
arXiv:2602.09864v1 Announce Type: new Abstract: Clustering heterogeneous relational data remains a central challenge in graph learning, particularly when interactions involve more than two types of...
arXiv:2602.09866v1 Announce Type: new Abstract: Figures of Speech (FoS) consist of multi-word phrases that are deeply intertwined with culture. While Neural Machine Translation (NMT) performs...
arXiv:2602.09868v1 Announce Type: new Abstract: Building on recent advances in video generation, generative video compression has emerged as a new paradigm for achieving visually pleasing...
arXiv:2602.09869v1 Announce Type: new Abstract: We study the performance of transformer architectures for multivariate time-series forecasting in low-data regimes consisting of only a few years...
arXiv:2602.09870v1 Announce Type: new Abstract: Steering methods influence Large Language Model behavior by identifying semantic directions in hidden representations, but are typically realized through inference-time...
arXiv:2602.09872v1 Announce Type: new Abstract: Human activity recognition (HAR) on wearable and mobile devices is constrained by memory footprint and computational budget, yet competitive accuracy...
arXiv:2602.09877v1 Announce Type: new Abstract: The emergence of multi-agent systems built from large language models (LLMs) offers a promising paradigm for scalable collective intelligence and...
arXiv:2602.09878v1 Announce Type: new Abstract: World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoning...