arXiv preprints from January 1, 2026 through July 28, 2026 — 23:24:44 EST
This paper introduces Project Synapse, a novel agentic framework designed for the autonomous resolution of last-mile delivery disruptions. Synapse employs a hierarchical multi-agent architecture in which a central Resolution Supervisor agent performs strategic task decomposition and delegates subtasks to specialized worker agents...
Explainable video anomaly detection (VAD) is crucial for safety-critical applications, yet even with recent progress, much of the research still lacks spatial grounding, making the explanations unverifiable. This limitation is especially pronounced in multi-entity interactions, where existing explainable VAD methods often produce...
The Andes Large area PArticle detector for Cosmic ray and Astronomy (ALPACA) is a new air-shower array experiment under construction in the Bolivian Andes, and its prototype ALPAQUITA surface array has been operating since 2023 April. In addition to the traditional $\ge$3-hit or $\ge$4-hit coincidences to trigger recording air-shower...
The paper studies a general norm minimization problem on a product of normed vector spaces. We establish dual necessary and sufficient optimality conditions and derive explicit formulas for the corresponding solution sets. These formulas are obtained under the assumption that one optimal solution together with its associated dual...
This paper investigates the Pareto boundary performance of a joint communication and sensing (JCAS) system that addresses both sensing and communication functions at the same time. In this scenario, a multiple-antenna base station (BS) transmits information to multiple single-antenna communication users while concurrently estimating...
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in vision-language understanding, yet how they internally integrate visual and textual information remains poorly understood. To bridge this gap, we perform a systematic layer-wise masking analysis across multiple architectures, revealing how visual-text fusion...
Flow cones of a directed acyclic graph admit a family of unimodular triangulations given by Danilov, Karzanov, and Koshevoy (DKK) whose normal fans are related to (generalizations) of the associahedron and permutahedron. A correspondence between these triangulations for certain graphs and maximal cones of a $g$-vector fan of a gentle...
Rich and informative profiling to capture user preferences is essential for improving recommendation quality. However, there is still no consensus on how best to construct and utilize such profiles. To address this, we revisit recent profiling-based approaches in recommender systems along four dimensions: 1) knowledge base, 2)...
Geometric Representation Learning (GRL) aims to approximate the non-Euclidean topology of high-dimensional data through discrete graph structures, grounded in the manifold hypothesis. However, traditional static graph construction methods based on Euclidean distance often fail to capture the intrinsic curvature characteristics of the...
Dietary flavonoids associate with disease prevention in epidemiological studies, yet their polypharmacological mechanisms remain unclear. We establish network pharmacology as a systematic framework to characterize flavonoid therapeutic properties through integrated computational, experimental, and epidemiological validation. We...
Existing circuit discovery methods rely on templated tasks with clean counterfactuals, limiting their use on diverse natural text. We adapt Contextual Decomposition for Transformers (CD-T) for unstructured settings via label-balanced activation means and task-directional relevance scoring, enabling counterfactual-free circuit...
The clustering of nucleons is a fundamental phenomenon with broad implications for nuclear physics and astrophysics. In this work, we employ a microscopic in-medium few-body approach to systematically investigate the formation and dissolution of light clusters (deuteron, $\rm{^3H}$, $\rm{^3He}$, $α$-particle) embedded in nuclear...
Flag codes generalize constant dimension codes by considering sequences of nested subspaces with prescribed dimensions as codewords. A comprehensive construction, which unites cyclic orbit flag codes, yields two families of flag codes on $\mathbb{F}^n_q$ (where $n=sk+h$ with $s\geq 2$ and $0\leq h < k$): optimum distance flag codes of...
This paper presents a gripper capable of grasping and recognizing terrain shapes for mobile robots in extreme environments. Multi-limbed climbing robots with grippers are effective on rough terrains, such as cliffs and cave walls. However, such robots may fall over by misgrasping the surface or getting stuck owing to the loss of...
This paper considers a downlink Reconfigurable Intelligent Surface (RIS)-assisted Joint Communication and Sensing (JCAS) system within a physically-consistent setting, accounting for the effect of mutual coupling between RIS elements arising due to sub-element spacing. The system features a multiple-input multiple-output (MIMO)...
Despite remarkable progress in large language models, Urdu-a language spoken by over 230 million people-remains critically underrepresented in modern NLP systems. Existing multilingual models demonstrate poor performance on Urdu-specific tasks, struggling with the language's complex morphology, right-to-left Nastaliq script, and rich...
The BESIII experiment at BEPCII provides a clean environment to test baryon-dark sector connections and baryon-number violation. Using $10^{10}$ $J/ψ$ events, searches were performed for $Σ^{+}\to p+\text{inv}$, $Ξ^{-}\toπ^{-}+\text{inv}$, and $\barΛ-Λ$ oscillations. No excess was observed, yielding $\mathcal{B}(Σ^{+}\to...
Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation (TTA) emerges as a predominant strategy to adapt VLMs to unlabeled test data on the fly. However, existing TTA methods heavily rely on zero-shot predictions as pseudo-labels for self-training,...
AI science evaluation tools aim to assess research credibility. As with traditional metrics such as impact factors, their edicts can be decontextualised and repurposed in problematic ways. To address this, I propose Critically-Engaged Pragmatism as a scientific norm enjoining scientific communities to scrutinise the purposes and...
Capacitively coupled discharges operated in mixtures of $Ar$ and $O_2$ are extensively utilized in plasma etching and deposition processes due to the oxidative properties and precursor functionality of the reactive species produced in the discharge. In $Ar$/$O_2$ discharges, the surface quenching coefficient of $O_2(a^{1}Δg)$ is known...
We demonstrate a dissipative protocol for ground-state preparation of a quantum spin chain on a trapped-ion quantum computer. As a first step, we derive a Kraus representation of a dissipation channel for the protocol recently proposed by Ding et al. [Phys. Rev. Res. 6, 033147 (2024)] that still holds for arbitrary temporal...
Diffusion and flow policies are gaining prominence in online reinforcement learning (RL) due to their expressive power, yet training them efficiently remains a critical challenge. A fundamental difficulty that distinguishes online RL from standard generative modeling is the lack of direct samples from the target Boltzmann distribution...
Device-edge collaborative inference with Deep Neural Networks (DNNs) faces fundamental trade-offs among accuracy, latency and energy consumption. Current scheduling exhibits two drawbacks: a granularity mismatch between coarse, task-level decisions and fine-grained, packet-level channel dynamics, and insufficient awareness of per-task...
The miscalibration of Large Reasoning Models (LRMs) undermines their reliability in high-stakes domains, necessitating methods to accurately estimate the confidence of their long-form, multi-step outputs. To address this gap, we introduce the Reasoning Model Confidence estimation Benchmark (RMCB), a public resource of 347,496...
Audio-visual semantic segmentation (AVSS) represents an extension of the audio-visual segmentation (AVS) task, necessitating a semantic understanding of audio-visual scenes beyond merely identifying sound-emitting objects at the visual pixel level. Contrary to a previous methodology, by decomposing the AVSS task into two discrete...