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Despite the variability in gene regulation and environmental conditions, development of an organism occurs through a sequence of highly coordinated patterning processes. Cells integrate different signals to accurately infer their position…
The high-pressure structural behavior of $\beta^\prime$-Mn$_3$(PO$_4$)$_2$ was investigated using synchrotron X-ray diffraction up to 20 GPa combined with density-functional theory calculations. At ambient conditions,…
Learning deployable manipulation policies is bottlenecked by the scarcity of data that is both high-fidelity and scalable. Real-robot teleoperation is accurate but costly to scale; robot-free UMI capture scales readily, and current practice…
Recent diffusion models have achieved remarkable realism in facial image synthesis, posing growing challenges to artificial intelligence-generated content (AIGC) forensic detectors.Existing evasion methods typically perturb pre-generated…
The ATLAS experiment has developed an extensive procedure based on Monte Carlo simulation and collision data to calibrate the response of large-radius jets. This paper describes the Run 2 calibration of large-radius jets reconstructed from…
We present a method for approximating real-time correlation functions and quantum transport coefficients of bosonic condensed phases. The direct evaluation of quantum real-time correlation functions in the path integral formulation is…
Evaluating AI agents in interactive environments is hindered by fragmented tasks, scaffolds, verifiers, and scoring rules. Existing efforts focus on narrow settings, remain limited in scale, or require costly reruns, leaving much of the…
AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizations. Existing security controls for coding agents are not systematically distributed to…
We study the intersection cohomology of minimally compactified Shimura varieties of PEL type AC using Igusa stacks and the work of Fargues-Scholze. More precisely, we construct a sheaf on the moduli stack of $G$-bundles on the…
This study identifies new depression biomarkers based on the dynamical properties of tract variables, which represent geometric features describing the configuration of the speech articulators. A key advantage of this approach lies in its…
This paper explores the effectiveness of domain adaptation techniques when using convolutional neural network (CNN)-based and transformer-based feature representations for acoustic scene classification. Two well-known domain adaptation…
Recursive self-improvement requires turning evidence of model failures into better models. Data-centric post-training research entails diagnosing capability gaps, designing and validating training-data strategies, and learning from…
In this paper, we present an automated data-driven workflow using Machine Learning (ML) for gas lift optimization in unconventional fields. This workflow integrates a ML model that accurately forecasts the Gas Lift Performance Curve, and a…
Deploying deep neural networks on resource-constrained hardware relies on mixed-precision quantisation (MPQ). current deployment toolchains severely fragment this process. Quantisation typically occurs as a hardware-agnostic preprocessing…
Agentic cloud management is emerging as a practice to automate laborious operations, minimize toil, and improve responsiveness. Despite the rapid development of autonomous management agents, we argue that the fundamental missing piece is a…
In this paper, we survey important results on the dynamics of permutable transcendental entire functions from 1958 to 2025. We have discussed the forms of transcendental entire functions that could be permutable. We have also discussed the…
We investigate how well large language models (LLMs) can assist scientific project planning and proposal evaluation. One-page project plans were independently generated for eight expert-conceived research projects in physics, astrophysics,…
LLM provenance testing asks whether a suspect LLM belongs to the same lineage as a source. Existing black-box methods largely infer this relationship from response-level characteristics, but these characteristics may shift under adaptation…
We consider the problem of state reconstruction for a nonlinear dynamical system from observations of a linear function of the state. We present a design method for a tunable observer and provide a general theorem which under certain…
We construct an incidence-driven tropical approximation of the planar Aleksandrov Monge--Amp\`ere equation. Let $\Omega\subset\mathbb R^2$ be a bounded open convex domain, let $K\Subset\Omega$, and let $F_N=G_{P_N}0_\Omega$ be the minimal…