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Four complementary roles organize the framework: an Organizational World defines operations management logic and an organizational behavior world model behind an enterprise from a strategic-institutional horizon; a Site World defines a physically bounded industrial optimization and execution world model from an
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Artificial Intelligence

https://arxiv.org/list/cs.AI/new
PL) Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose combined execution contract remains external

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https://arxiv.org/pdf/2006.02318
3/ pdfx PDF/X Schema external URL to an online version or preprint AuthoritativeDomain Text http://www

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

Information Theory

https://arxiv.org/list/cs.IT/new
The physical world is not changed by a reconfiguration of the observer, but its complex representation in the observation world is

Forthcoming in SIAM Journal on Financial Mathematics Decentralised

https://arxiv.org/html/2309.08431v3
3 Discussion: profitability, PL, and concentration risk 4

Cryptography and Security

https://arxiv.org/list/cs.CR/new
Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Cryptography and Security New submissions Cross-lists Replacements See recent articles Showing new listings for Friday, 7 August 2026

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

https://arxiv.org/html/2608.03573v1
Multi-Task Learning Paradigms for LLMs 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

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

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https://arxiv.org/pdf/1811.12628
ioªAJÃyØU§±Æ# LFg”À¡ë‡C}Âz¾¹OÒ7ÜtŸXW,Û½¸×·Ý­ÔDZ¤¥bùé�¹n‡‘;• æ] ,¡=h粂7'�6m·¯.>×tÐØv Á}u/ÔÇ|8à ÏÈp­qMùP7õøš™f3îE()Ö½”‡—a¬Ž\¾×ÉÅdYD3²,V:…A3•™„ýñ K+r ‰Ó è:ßtåî 4�!÷ð4}w¨áƒóLožñd»þ#×äà±­È6?úq2UdQL %Ê”‰c7Ð_®·Vo¾§ßïÓÿ1‘q½o

Report GitHub Issue

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

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

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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv

Mitigating Distribution Shift in Stock Price Data via Return-Volatility

https://arxiv.org/html/2508.20108v2
Extensive experiments on real-world datasets demonstrate that ReVol enhances the performance of the state-of-the-art backbone models in most cases, achieving an average improvement of more than 0

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
However, most RL methods face difficulties when applied in the real world due to three factors: input, output, and the cycle-flow relation

Multi-Currency AMMs for Decentralized FOREX Markets: Feasibility

https://arxiv.org/html/2607.26405v1
After World War II, the stable US economy with its dollar attached to the gold standard made it an attractive peg codified through the 1944 Bretton Woods Agreement

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

Stochastic Choice with Advertising

https://arxiv.org/html/2608.03504v1
com/wp-content/uploads/2025/04/IAB_PwC-Internet-Ad-Revenue-Report-Full-Year-2024

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

1 Introduction

https://arxiv.org/html/2511.06451v1
6 Experiments Compute, code, and seeds

On the Complexity of Learning to Cooperate with Populations of Socially

https://arxiv.org/html/2407.00419v1
nl Abstract Artificially intelligent agents deployed in the real-world will require the ability to reliably cooperate with humans (as well as other, heterogeneous AI agents)

Data Structures and Algorithms

https://arxiv.org/list/cs.DS/new
If the input strings have lengths $N$ and $M$, and their run-length encodings have $n$ and $m$ runs, respectively, the algorithm runs in $O(mN+nM)$ time using $O(nm)$ space

Machine Learning Dec 2022

https://arxiv.org/list/cs.LG/2022-12
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 Machine Learning Authors and titles for December 2022 Total of 2004 entries : 1

Raising Rivals’ Costs on Hybrid Platforms: The Complementarity of Fees

https://arxiv.org/html/2608.02800v1
com in China, Walmart Marketplace and Target Plus in the United States, Otto in Germany, Flipkart in India, and Rakuten in Japan

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

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
Sayed are with the Adaptive Systems Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Switzerland

Homogeneous Distributed Observers for Quasilinear Systems

https://arxiv.org/html/2407.05763v1
fr Inria, Centrale Lille, Université de Lille, CNRS, CRISTAL, France

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https://arxiv.org/src/1910.03771
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https://arxiv.org/src/2104.08691
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https://arxiv.org/pdf/2608.03494
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