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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
We demonstrate that it can self-assemble functional circuits from scratch and rapidly re-route logic around permanent, previously unseen hardware faults

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

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https://arxiv.org/html/2609.03371v1
Operators can replace or upgrade their instruments and distribute longitude coverage across a network

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
This paper reviews recent theoretical developments on research design for policy choice and provides new tools applied researchers can use to guide their design choices and communicate their policy recommendations

Mathematics

https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks

Computation and Language

https://arxiv.org/list/cs.CL/new
LG) Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed

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

Asking Questions the Right Way: A Multi-Agent Conversational System for

https://arxiv.org/html/2608.01366v2
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts

On the Diversity of Analogy Making in Large Language Models

https://arxiv.org/html/2608.03233v1
This example demonstrates how greater analogy diversity enables broader knowledge integration and can foster scientific discovery, motivating our study of analogy diversity in large language models

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https://arxiv.org/pdf/2608.03233
T½+Ñj¬±qø8¸ ÇM\¯c¡¤~wD`ž”Œõ%::P ÏsC`à zßzæ¯TrÔêH`$Å{0‡ÝF{ÿìŒkëʆêÃÆ„Ð endstream endobj 411 0 obj > stream On the Diversity of Analogy Making in Large Language ModelsYuanhao ShenDaniel Xavier de SousaCaio César Sifuentes BarcelosHongyu GuoXiaodan Zhuhttp://arxiv

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https://arxiv.org/html/2609.02852v1
However, various strands of evidence indicate that an LLM’s externalized linguistic outputs and mechanistically-extracted linguistic features can be an unreliable lens for understanding internal model computation

Width, Memory, and Delay: A Resource Accountingfor the Limits of Flat

https://arxiv.org/html/2608.00028v1
Abstract A recurring question in the design of scalable multi-agent systems—from robot swarms to collectives of large-language-model (LLM) agents—is whether adding more agents can, on its own, overcome performance limits, or whether a qualitatively deeper organization is required

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https://arxiv.org/html/2609.03103v1
This geometry offers an efficient compromise among survey coverage, pointed sensitivity, system complexity, and resilience, and can be scaled to larger persistent soft X-ray monitoring architectures

Reviving Micro Real Rigidities: The Importance of Demand ShocksThe views

https://arxiv.org/html/2608.02817v1
expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. The authors are grateful for the invaluable feedback they received on an earlier draft from Jón

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/2608.02122
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https://arxiv.org/pdf/2608.01785
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https://arxiv.org/pdf/2407.00125
document was published isbn Text external ISBN for the publication in which the document was published doi Text external Digital Object Identifier for the document url URL external URL at which the document can be found byteCount Integer internal Approximate file size in octets pageCount Integer internal Number of

[2608.12700] A Contract-Grade Verifier for LLM-Generated GPU Kernels

https://arxiv.org/abs/2608.12700
A kernel can pass that test and still be silently wrong

[2204.04218] Multimodal Multi-Head Convolutional Attention with Various

https://arxiv.org/abs/2204.04218
In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques capture several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results

Asymptotic Equivalence of Immediate and Deferred Acceptance

https://arxiv.org/html/2607.24970v2
A well-known modification of this algorithm allows schools to consider applications even when they are already full, so that schools can reject previously accepted students in favour of higher-priority late applicants

Distributed, Parallel, and Cluster Computing

https://arxiv.org/list/cs.DC/new
SE) Automating GPU kernel optimization remains difficult in practice: generated variants can violate correctness constraints, runtime measurements are noisy, and search often stalls early

Untitled Document

https://arxiv.org/html/2607.28294v1
This analogy is useful but, as demonstrated here, it can be misleading for asymptotic inference, and the bootstrap theory

Numerical Analysis

https://arxiv.org/list/cs.NA/new
NA) Imaging a target sample in near-field scanning optical microscopy (NSOM) is fundamentally limited by measurement artifacts and data contamination from multiple probe-sample scattering

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

https://arxiv.org/html/2508.20101v1
In an empirical application, we demonstrate how the model can be applied to financial stock networks

Microstructural Foundations of Rough Noise1footnote

https://arxiv.org/html/2607.29442v2
That is, does there exist a tick-by-tick model, replicating the salient features of ultrahigh-frequency prices, whose scaling limit is of the form Yt=Xt+ZtY_{t}=X_{t}+Z_{t} with ZZ a continuous-time rough process

Computation and Language

https://arxiv.org/list/cs.CL/recent
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 Computation and Language Authors and titles for recent submissions Wed, 5 Aug

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

https://arxiv.org/html/2412.12213v2
Importantly, FINN extends beyond liquid option markets: it can be trained directly on historical spot prices to construct coherent option prices and Greeks for assets with no listed options

1 Introduction

https://arxiv.org/html/2508.02739v1
2 Preliminary 3 Methodology K-line Tokenization Hierarchical Autoregressive Modeling Model Pre-training Dataset Model Training Inference 4 Experiments Experimental Setup Main Results Prediction Tasks Generative Tasks Investment