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arXiv:2601.18740v1 Announce Type: new Abstract: This paper presents a novel indoor visible light positioning (VLP) system utilising one vertical-cavity surface-emitting laser installed at the ceiling...
arXiv:2601.18744v1 Announce Type: new Abstract: Time series data is ubiquitous in real-world scenarios and crucial for critical applications ranging from energy management to traffic control....
arXiv:2601.18745v1 Announce Type: new Abstract: We investigate the problem of safety verification of infinite-state parameterized programs that are formed based on a rich class of...
arXiv:2601.18747v1 Announce Type: new Abstract: Modern information retrieval is transitioning from simple document filtering to complex, neuro-symbolic reasoning workflows. However, current retrieval architectures face a...
arXiv:2601.18748v1 Announce Type: new Abstract: We establish a spectral gap for Continuum Glauber dynamics on the hard sphere model assuming strong spatial mixing, thereby extending...
arXiv:2601.18749v1 Announce Type: new Abstract: The automatic generation of pull requests (PRs) using AI agents has become increasingly common. Although AI-generated PRs are fast and...
arXiv:2601.18750v2 Announce Type: new Abstract: Mixed Reality (MR) interfaces increasingly rely on gaze for interaction , yet distinguishing visual attention from intentional action remains difficult,...
arXiv:2601.18751v1 Announce Type: new Abstract: Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise trajectory comparisons. However, real-world...
arXiv:2601.18753v1 Announce Type: new Abstract: The reliability of Large Language Models (LLMs) in high-stakes domains such as healthcare, law, and scientific discovery is often compromised...
arXiv:2601.18754v1 Announce Type: new Abstract: Autonomous unmanned aerial vehicle (UAV) systems are increasingly deployed in safety-critical, networked environments where they must operate reliably in the...
arXiv:2601.18758v1 Announce Type: new Abstract: In this work, we design and analyze semi/fully-discrete virtual element approximations for the time-dependent Navier--Stokes-Cahn--Hilliard equations, modeling the dynamics of...
arXiv:2601.18759v1 Announce Type: new Abstract: Designing user interfaces (UIs) is a critical step when launching products, building portfolios, or personalizing projects, yet end users without...
arXiv:2601.18760v1 Announce Type: new Abstract: A crucial consideration when developing and deploying Large Language Models (LLMs) is the human values to which these models are...
arXiv:2601.18761v1 Announce Type: new Abstract: Recent data protection and data governance regulations have intensified the demand for interoperable, decentralized data ecosystems that can support not...
arXiv:2601.18763v1 Announce Type: new Abstract: Most of the contemporary literature on information freshness solely focuses on the analysis of freshness for martingale estimators, which simply...
arXiv:2601.18765v1 Announce Type: new Abstract: Autonomous robotic systems are widely deployed in smart factories and operate in dynamic, uncertain, and human-involved environments that require low-latency...
arXiv:2601.18771v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks, particularly when augmented with search mechanisms that enable...
arXiv:2601.18772v1 Announce Type: new Abstract: Recent discussions at the intersection of journalism, HCI, and human-centered computing ask how technologies can help create reader-oriented news experiences....
arXiv:2601.18777v1 Announce Type: new Abstract: Evaluating the quality of search, ranking and RAG systems traditionally requires a significant number of human relevance annotations. In recent...
arXiv:2601.18778v1 Announce Type: new Abstract: Can a model learn to escape its own learning plateau? Reinforcement learning methods for finetuning large reasoning models stall on...
arXiv:2601.18779v1 Announce Type: new Abstract: Reinforcement learning (RL) has improved the reasoning abilities of large language models (LLMs), yet state-of-the-art methods still fail to learn...
arXiv:2601.18783v1 Announce Type: new Abstract: Balancing safety, efficiency, and operational costs in highway driving poses a challenging decision-making problem for heavy-duty vehicles. A central difficulty...
arXiv:2601.18785v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has enabled a new paradigm for bridging authorial intent and player agency in...
arXiv:2601.18788v1 Announce Type: new Abstract: Unsupervised text segmentation is crucial because boundary labels are expensive, subjective, and often fail to transfer across domains and granularity...