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We define a new class of superalgebras, called higher-level degenerate spin affine Hecke superalgebras, and study their structure theory. We establish an isomorphism that relates the higher-level degenerate spin affine Hecke superalgebras…

GUI agents have the potential to become a general purpose executor over existing digital devices. To advance them toward real-world use, we envision agents that operate reliably on real devices, execute workflows across platforms, combine…

World models give embodied AI a predictive core: they compress observations into states, simulate action-conditioned futures, and enable planning beyond reactive control. This predictive layer, however, opens a new security…

Agentic vision-language models (VLMs), which interleave textual reasoning with explicit tool calls such as cropping and code-based image manipulation, have emerged as a compelling paradigm for reliable and interpretable multimodal…

This paper presents a Cram\'er-Rao lower bound (CRLB)-driven beamforming (BF) and power allocation (PA) framework for cooperative integrated sensing and communication (ISAC) networks, where a set of multi-antenna base stations (BSs) jointly…

GPU cluster operators cannot predict how long pending workloads will wait for admission. Existing systems use greedy heuristics with no formal wait time guarantees. We formalize GPU cluster admission as a multi-class, multi-resource…

This paper studies whether AI automation can improve organizational outcomes by reducing variance when collecting information. We conducted a large-scale natural field experiment in which 70,000 job applicants were randomly assigned to be…

Let $g\in H(\mathbb D)$, the generalized Hilbert operator $\mathcal H_g$ is defined by \[ \mathcal H_g(f)(z)=\int_0^1 f(t)g'(tz)dt,\ \ z\in \mathbb D\, \ \ f \in H(\mathbb D). \] Let $\mathcal R_p=\mathcal H(H^p)$ be the range of the…

Atmospheric predictability declines rapidly beyond the next ten days, such that forecasts at longer lead times primarily convey large-scale trends rather than specific states. Yet in a warming world, improving early warnings of extreme heat…

Hash Chemistry is a family of minimalistic evolutionary models in which a deterministic hash function assigns a scalar score to entities of arbitrary size, opening a combinatorially vast possibility space (a ``cardinality leap''). Since its…

Ensuring the accuracy and consistency of clinical trial Tables, Figures, and Listings (TFLs) remains a major challenge in regulatory reporting. Independent programming and manual review are essential quality-control practices, but…

Generative design artificial intelligence (AI) tools are currently used in multiple scientific fields, yet their adoption in mechanical engineering computer-aided design (CAD) remains limited due to a lack of disseminated case studies,…

With the increasing need for remote work, especially since the COVID-19 era, Remote Desktop Services (RDS) have become widely used. Because interactive RDS usage depends heavily on communication quality, some studies have investigated the…

We study parametric classes of almost stochastic dominance on general Polish spaces as order relations for probability distributions with a parameter $\gamma \in [0,1]$. Larger values of $\gamma$ correspond to weaker order relations:…

We study properties of domain walls (DWs) arising in the model with a double well potential assuming different early universe cosmologies: from dust through stiff matter domination to the limit of effective Minkowski space. Using lattice…

This paper presents the first conducted-interference measurements of a commercial Very Low Power (VLP) Wi-Fi 6E/7 device into both the gNB uplink and UE downlink receiver chains of a live 5G New Radio (NR) system, using a complete O-RAN/SDR…

Causal discovery in multivariate time series data is challenging due to complex interactions, high dimensionality, and nonlinear dependencies among variables. Existing methods often struggle to capture these complexities, resulting in…

Vision-Language Models (VLMs) such as CLIP are now foundational to multimodal systems, yet their robustness to spurious correlations remains poorly understood at scale. We present the first large-scale empirical study of 194 publicly…

Explaining physical phenomena is central to physics learning, because students' explanations provide evidence of their conceptual understanding. Because conceptual understanding can only be inferred through language rather than observed…

We establish the equivalence between homogeneous and isotropic linearized gravity with minimally coupled degrees of freedom and the Caldeira--Leggett model of open systems. This connects gravitation to an established system-plus-reservoir…