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This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
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Artificial Intelligence

https://arxiv.org/list/cs.AI/new
First-author implementations of a standards composition and a separate Sismic statechart reproduce the tested cold-chain trace

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
org perpetual non-exclusive license arXiv:2607

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https://arxiv.org/html/2609.03159v1
The Accretion Explorer Interferometer NIAC Phase I Study Team Principal Investigator: Kimberly A. Weaver (NASA/GSFC, Code 662) Co-Investigators: Kenneth Carpenter (NASA/GSFC, Code 667) Maurice Leutenegger (NASA/GSFC, Code 662) Takashi

Cryptography and Security

https://arxiv.org/list/cs.CR/new
CyberBridge supports three primary use cases; (1) job recom- mendation, providing students with vacancies and closely match- ing professional roles based on their completed curriculum, (2) market analysis, enabling educators and curriculum developers to analyze which roles ar

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
2 pp, exceeding MemSearch reader scaling (+10

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

Finance-Informed Neural Network: Learning the Geometry of Option Pricing

https://arxiv.org/html/2412.12213v2
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

Computation and Language

https://arxiv.org/list/cs.CL/new
3% coverage), and a visual tablet renderer, packaged as a pip-installable toolkit with CLI and web demo

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https://arxiv.org/html/2401.02063v2
A’ohoku Place, Hilo, HI 96720, USA    Sarah Antier Affiliation: Observatoire de la Côte d’Azur, Université Côte d’Azur, Boulevard de l’Observatoire, 06304 Nice, France    Erik Blaufuss Affiliation: Department of Physics, University of Maryland, College Park, MD 20742, USA    P

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
Causal regularisation yields reductions above 90% at the tested positive penalty weights, but with larger predictive and risk-return trade-offs

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
Claude Opus 5 and Fable 5 provided research assistance throughout, spanning code development, data construction and empirical analysis, and the drafting of the manuscript

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Vision and Pattern Recognition New submissions Cross-lists Replacements

Mathematics

https://arxiv.org/list/math/new
It is natural to expect that if many pairs $(x_i,x_j)$ lie at distance close to $1$ from each other, then some clustering phenomenon must occur, implying that a significant number of these pairs are also very close to each other

[cond-mat/9406071] Solvent-induced organization: A physical model of

https://arxiv.org/abs/cond-mat/9406071
The model is then tested by being employed in a simulation scheme designed to mimic solvent effects

Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems

https://arxiv.org/html/2407.03956v3
This system tackles the complex puzzle-solving task by breaking down the problem into smaller, manageable parts, generating SMT (Satisfiability Modulo Theories) code to solve them with a theorem prover, and using feedback between the agents to repeatedly improve their answers

Computational Engineering, Finance, and Science

https://arxiv.org/list/cs.CE/new
The source code for all six methods, including the train

Where does the criticality live? Early-warning signals are event

https://arxiv.org/html/2607.27070v1
com Abstract Do crypto perpetual-futures crashes carry a reproducible early-warning fingerprint of a critical transition, and in which state variable

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https://arxiv.org/html/1802.00048v2
Our results show that all tested agents are vulnerable to several kinds of deception, but that different agents have different weaknesses

Collaborative Adaptation for Recovery from Unforeseen Malfunctions in

https://arxiv.org/html/2407.19144v1/
These malfunctions decrease the team’s ability to accomplish assigned task(s), especially if they occur after the learning algorithms have already converged onto a collaborative strategy

Identification of phase correlations in Financial Stock Market

https://arxiv.org/html/2508.20105v2
Turbulence A Introduction A.1 Stock Market and Turbulence A.2 Market dynamics and Computational Approach B Research Gap C Research objective D Proposition E Research Methods E.1 Tools and Techniques E.2 Extended Fourier Transform E.3

Report GitHub Issue

https://arxiv.org/html/2608.03372v1
org  GitHub sourcecontextcandidatememoryalign claimscontent-word overlapseven checkspolarity ⋅\cdot condition ⋅\cdot temporalhedge ⋅\cdot attributionbrittle ⋅\cdot truncatedflagsevidence + citationverdict policyhard-codedpasspass_w_flagsrewriterejectuncheckablenever a passwitness (optional)one sentence, one

On the Non-Specificity of Statistical Measures Used in Script

https://arxiv.org/html/2608.02999v1
org perpetual non-exclusive license arXiv:2608

Condensed Matter

https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries