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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
A core calculus gives an effect-confinement lemma and six safety properties

Probing Character-level Transformers for the Spanish L-shaped Morphome

https://arxiv.org/html/2608.03452v1
de Abstract When a transformer learns an irregular morphological pattern, what has it learned

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

Information Theory

https://arxiv.org/list/cs.IT/new
all New submissions (showing 11 of 11 entries) [1] arXiv:2608

Cryptography and Security

https://arxiv.org/list/cs.CR/new
fewer | more | all New submissions (showing 32 of 32 entries) [1] arXiv:2608

Eliminating Majority Illusion is Easy

https://arxiv.org/html/2407.20187v1
1 Introduction 1.1 The Illusion Elimination Problem 1.2 Our Contributions. 1.3 Related Work. 2 Preliminaries 3 Majority Illusion Addition Elimination (MIAE) 3.1 A First Attempt 3.2 A Second Attempt 3.3 A TDI System 3.4 A Polynomial Time

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of

https://arxiv.org/html/2608.03573v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/1811.12628
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Mathematics

https://arxiv.org/list/math/new
up to 2000 entries per page: fewer | more | all New submissions (showing 219 of 219 entries) [1] arXiv:2608

Report GitHub Issue

https://arxiv.org/html/2607.22511v2
The source code, formal library, and run records are available at https://github

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

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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv

1 Introduction

https://arxiv.org/html/2511.06451v1
1 Data Protocol (arXiv Release) Synthetic risk–neutral generator

Report GitHub Issue

https://arxiv.org/html/2608.02609v1
Code and pretrained model: https://github

Approximating Choice Data by Discrete Choice Models

https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset M Additional Empirical Application: Fishing-site Choice M

On the Complexity of Learning to Cooperate with Populations of Socially

https://arxiv.org/html/2407.00419v1
Two natural assumptions in such settings are that: 1) all agents in the population are individually rational learners, and 2) when any two members of the population are paired together, with high-probability they will achieve at least the same utility as they would under some Pareto efficient equilibrium strategy

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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2006.02318
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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

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https://arxiv.org/pdf/2608.01785
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Data Structures and Algorithms

https://arxiv.org/list/cs.DS/new
per page: fewer | more | all New submissions (showing 7 of 7 entries) [1] arXiv:2608

Report GitHub Issue

https://arxiv.org/html/2608.02942v1
org perpetual non-exclusive license arXiv:2608

Mitigating Distribution Shift in Stock Price Data via Return-Volatility

https://arxiv.org/html/2508.20108v2
Normalization for Accurate Prediction 1 Introduction 2 Related Works 2.1 Geometric Brownian Motion 2.2 Deep Learning-Based Stock Price Prediction 2.3 Methods for Addressing Distribution Shift 3 Proposed Method 3.1 Overview 3.2 Return

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
II RELATED WORK II-A Traditional methods II-B RL methods. III PRELIMINARIES IV METHOD IV-A RL Setup IV-B Network design IV-C Training IV-D Theoretical Analysis V EXPERIMENT V-A Towards Real-world Dataset and Simulation V-B Benchmark

Multi-Currency AMMs for Decentralized FOREX Markets: Feasibility

https://arxiv.org/html/2607.26405v1
& Optimal Design 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

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
2 Proof of Lemma 1 (Optimality of Boundary Crossing) D

Mathematical Finance Apr 2021

https://arxiv.org/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3

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

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
7Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
This would require the manager to collect this information from the players, and then solve a large-scale optimization problem