1614479 results (page 7 of 64580)
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An Infrastructure-less, Control-Independent Solution to Relative Localisation of a Team of Mobile Robots using Ranging Measurements
The ability to localise teams of robots is essential for applications ranging from robotic fleets in unstructured environments to cooperative control and navigation tasks. In such contexts, fixed infrastructure is often unavailable, deployments must be fast and flexible, and system requirements must be minimal. We present a decentralised cooperative localisation algorithm that addresses all these …
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Judging to Improve: A De-biased VLM-as-3D-Judge Protocol for Single-Image 3D Generation
A companion study established a de-biased, cross-model VLM-as-3D-judge that reliably ranks single-image-to-3D mesh quality where cheap geometry and CLIP proxies fall short. This paper asks: can that judge's preferences specialize a strong open generator, TRELLIS, on one asset class (furniture), cheaply and without human labels? Taking the judge from ranking to optimization is where the work lives.…
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Automating SKILL.md Generation for Computer-Using Agents via Interaction Trajectory Mining
Explicit skill libraries make computer-using agents easier to inspect, but it remains unclear whether such libraries can be mined from interaction data in a way that improves downstream policies. We study this question through a three-stage pipeline that segments GUI trajectories, clusters segments into candidate skills, and trains a skill-aware policy from the resulting annotations. The mined clu…
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Sparse add-on controller design: A Youla approach to system-level performance
The performance of high-tech systems is often dictated by a few performance objectives shared among the many closed-loop controlled subsystems operating in the machine, such as synchronization, coordination, and alignment, which necessitates control methods that explicitly address them to achieve optimal performance. The aim of this paper is to introduce a framework that improves system performanc…
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Lightstack: A Python Package for Creating Photometric Data Cubes
Multi-band photometry traces diverse physical processes across a wide range of wavelengths. In recent decades, this field has been driven by the rapid growth of multi-imaging datasets, from high-resolution observation from Hubble Space Telescope and James Webb Space Telescope to the forthcoming large-scale surveys enabled by the Roman Space Telescope and Rubin Observatory, for example. In this wor…
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Train, Retrieve, or Both? A Four-Arm Head-to-Head for Correct Statutory Citation on the Ontario Residential Tenancies Act
Self-represented tenants, landlords, and help-desk staff need to be pointed at the provision of law that actually governs a question, with a correct statutory citation. We study this task on the Ontario Residential Tenancies Act, 2006 (RTA) and its core regulation, asking the operator's question empirically: is fine-tuning enough, or is hybrid retrieval needed? We run a four-arm head-to-head on Qw…
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On the Variance of Temporal Difference Learning and its Reduction Using Control Variates
We analyze the variance of temporal difference (TD) learning using the phased setting with tabular representation, and show that one of the mechanisms behind its ability to reduce variance is by effectively aggregating over a larger number of independent trajectories. Based on this insight, we demonstrate that (1) the variance of TD is asymptotically bounded from above by Monte Carlo (MC) estimato…
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Robust $Q$-learning for mean-field control under Wasserstein uncertainty in common noise
In this article, we present a robust $Q$-learning algorithm for discrete-time mean-field control problems under Wasserstein uncertainty in the common noise law. The algorithm combines a quantization-and-projection scheme with a Wasserstein dual reformulation on the common-noise space. We establish its convergence together with finite-time iteration bounds for both synchronous and asynchronous lear…
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A long-term spectro-temporal study of Jovian X-ray and Ultraviolet response to solar activity
We present results from a multi-decade investigation of solar activity-driven variability in Jupiter's emissions, using solar X-ray flux and sunspot numbers as activity indicators and ultraviolet (UV) and X-ray observations from the International Ultraviolet Explorer (IUE; 1978-1996) and the Chandra X-ray Observatory (2011-2021). Analysis of 51 high-SNR UV spectra spanning two solar cycles shows t…
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A cubical formalisation of conditional independence, Bayesian conditioning, and Pearl's d-separation soundness
The standard convex-algebra interchange axiom, common to probability-monad formalisations since Stone, is provably too weak to support full Bayesian conditioning. We make this precise in Cubical Agda: finite distributions as a higher inductive type, conditional independence as a cubical path between kernels, recursive Bayesian conditioning as a total function on a full-support fragment. Lifting co…
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V7995 Sgr: A New FU Orionis Accretion Outburst Near NGC 6589/6590
We announce a new FU Orionis type outburst that reached peak brightness in late 2024, following a steep 4.6 month photometric rise of -2.85 mag in the $r$ band. This rapid brightening at all wavelengths was preceeded in the infrared by a much shallower rise over 4 years. The progenitor object was an unstudied young stellar object having a flat-spectrum type spectral energy distribution, and extend…
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Counting q-Matroids
$q$-Matroids, a $q$-analogue of classical matroids have attracted a lot of attention over the last decade, yet their enumeration remains largely unexplored. In this paper, we study the number of $q$-matroids, paving and sparse-paving $q$-matroids defined on a fixed ground space and with prescribed rank. We derive new lower bounds using constructions from constant-dimension codes and improve existi…
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Critical Percolation as a Synthetic Data Model for Interpretability
Neural networks learn features that reflect the hierarchical, multi-scale structure of natural data. Synthetic datasets used to evaluate interpretability methods typically lack this structure, limiting their value as realistic toy models. To close this gap, we introduce a family of synthetic datasets consisting of hierarchical functions defined on critical mean-field percolation clusters embedded …
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Effective discrete-modulated continuous variable QKD under general attacks
Continuous variable quantum key distribution via discrete modulations ensures information-theoretic security using standard telecom technologies, providing affordable and scalable quantum communications with simplified classical postprocessing. However, existing security proofs against general attacks often rely on restrictive assumptions, such as a bounded dimension for coherent states, or requir…
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Synchronization modes in bipartite oscillator networks
Collective oscillations in neuronal systems often arise from interactions between excitatory and inhibitory populations rather than from recurrent coupling within a single ensemble. Motivated by the coexistence of strongly and partially synchronized regimes in such systems, we study the Kuramoto Sakaguchi model on a bipartite network. Despite its minimal structure, the model exhibits rich collecti…
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Quantum ring all-reduce: communication and privacy advantages for distributed learning
Machine learning models have scaled to unprecedented sizes, making training across distributed devices the de facto standard in the field. In this work, we explore how quantum communications can make distributed training both more communication-efficient and information-theoretically private, for both classical and quantum learning models. Ring all-reduce is the foundational communication primitiv…
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Anchors Away: Navigating Unanchored Indirect Comparisons with Multilevel Unanchored Meta-Regression (ML-UMR)
Unanchored indirect treatment comparisons using single-arm studies or disconnected evidence are increasingly used in health technology assessment (HTA) when randomized evidence is unavailable. Existing methods, including matching-adjusted indirect comparison (MAIC) and simulated treatment comparison (STC), are generally limited to pairwise settings and typically estimate marginal effects in the co…
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Phase locking nuclear spins in silicon with spin-orbit coupling
Because they have such long coherence times, nuclear spins have extraordinary potential for use in quantum information processing devices. However, coherent nuclear spin control generally requires external phase references, such as microwave control fields. Here, we phase-lock a $^{29}$Si nuclear spin ensemble in a silicon quantum dot using only the internal electronic spin-orbit coupling as a pha…
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Stuttering Classification and Segmentation with Attention-Based Multiple Instance Learning
Stuttering detection and classification using deep learning methods has the potential to improve the process of stuttering severity assessment. Most stuttering classification datasets provide clip-level labels, making them unsuitable for fine-grained frame-level classification needed to determine the duration of individual stuttering dysfluencies. To overcome this challenge, we present a multiple …
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Instruments for Focal Plane X-Ray Polarimetry in the Next Decade
The successful detection of X-ray polarization from many celestial sources belonging to different classes by the IXPE mission has opened a new window in X-ray astronomy. While an impressive number of scientific topics have already been addressed by IXPE, many of them would benefit from a new class of instrumentation that could be launched on a relatively short time scale. In this contribution, we …
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Autonomous Driving with Priority-Ordered STL Specifications Under Multimodal Uncertainty
Autonomous vehicles must plan trajectories that satisfy a multitude of requirements on safety, passenger comfort, and compliance with traffic rules. However, in safety-critical scenarios, it is not always possible to satisfy all requirements simultaneously, necessitating their prioritization based on importance. At the same time, in these safety-critical scenarios, the uncertainty in trajectory pr…
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A merger shock traced by radio arcs and ultra-long radio tails in galaxy cluster A2142
Abell 2142 (A2142) is a massive, nearby galaxy cluster undergoing a complex merger. It exhibits an elongated X-ray morphology along the northwest-southeast axis and hosts four known cold fronts. Using XMM-Newton observations, we detect a merger shock on the northwest side of the cluster with a Mach number of $M \sim 1.3$. The observed shock front and four cold fronts can be reproduced by numerical…
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The magic of the gravitational vacuum
The black hole information paradox challenges us to do something that is seemingly impossible: find a violation of the semiclassical approximation in a region where all curvatures are low. The vecro hypothesis proposes a structure of the gravitational vacuum that can accomplish this task. In this article we explain the hypothesis, and give a lattice model to describe the essence of its idea. The H…
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SoftSkill: Behavioral Compression for Contextual Adaptation
Agent skills are commonly deployed as natural-language Markdown files that encode answer policies, evidence-use habits, and task procedures. These files are readable and portable, but they are consumed indirectly: for each task instance, a frozen language model must translate a long textual artifact into generation-time behavior. This paper asks whether a natural-language skill can instead initial…
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Data dependent Shepard approximation through and adaptive modification of the shape parameter
In this article, we introduce a novel data-dependent Shepard interpolation method inspired by the adaptive strategies proposed in [2]. In this case, as Shepard interpolation does not produce oscillations, our approach has the core objective of reducing the smearing near jump discontinuities in the data in one and two dimensions. While the original work in [2] focuses in on Radial Basis Function (R…