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

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

https://arxiv.org/html/2608.03452v1
Can such a complex pattern be learned from exposure to inflected forms alone

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

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
Dispersing the rebalance through the session, Korea’s chosen remedy, moves the order but not the reference that sizes it and can raise the toll

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

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
If we make no assumptions about the target population, we can do little more than attempt to mimic observed behavior as closely as possible, reducing the problem to one of imitation learning

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
For real-world solutions, only flow can be reliably collected, whereas common RL methods need more

Mitigating Distribution Shift in Stock Price Data via Return-Volatility

https://arxiv.org/html/2508.20108v2
How can we address distribution shifts in stock price data to improve stock price prediction accuracy

Multi-Currency AMMs for Decentralized FOREX Markets: Feasibility

https://arxiv.org/html/2607.26405v1
Despite this growth, foreign exchange transfers follow a peculiar arrangement: most currency pairs do not trade directly with one another but route through the US dollar (USD)

Report GitHub Issue

https://arxiv.org/html/2607.22511v2
1 Introduction Language models can now generate research artifacts—conjectures, proofs, experiments, and complete papers—more rapidly than they can be evaluated

Stochastic Games with Minimally Bounded Action Costs

https://arxiv.org/html/2407.18010v2
We prove the game respects a dynamic programming principle and that the Markov perfect equilibrium can be computed as a limit point of a sequence of Bellman operations

Stochastic Choice with Advertising

https://arxiv.org/html/2608.03504v1
org perpetual non-exclusive license arXiv:2608

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

https://arxiv.org/html/2412.12213v2
8 Learning Prices Where Option Markets Do Not Exist 4

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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

On the Non-Specificity of Statistical Measures Used in Script

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

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
Although several related problems can be transformed into comparable forms [redaud2022stabilizing], they do not directly address the PIDE setting considered here

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

Report GitHub Issue

https://arxiv.org/html/2608.02609v1
edu Abstract 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

Maximizing utility in multi-agent environments by anticipating the

https://arxiv.org/html/2407.04889v1
(2019b); however, in general settings it is not known how to best play against mean-based learners, even if the agent knows everything about the learners, and can predict with certainty what actions they would take as a function of the history of play

Asymptotic Equivalence of Immediate and Deferred Acceptance

https://arxiv.org/html/2607.24970v2
That total number of applications mirrors the classical coupon-collector problem: if each breakfast cereal box contains one of nn equally likely coupons, how many cereal boxes do I need to buy to collect all nn coupons

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
The global performance at NE can be improved by imposing linear constraints on the NE, also known as a generalized Nash equilibrium (GNE)

Cryptography and Security

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

Existence of Richter–Peleg representation for general preferences

https://arxiv.org/html/2508.08980v3
org perpetual non-exclusive license arXiv:2508

Eliminating Majority Illusion is Easy

https://arxiv.org/html/2407.20187v1
If so, can we do this optimally in polynomial time

United We Stand: Decentralized Multi-Agent Planning With Attrition

https://arxiv.org/html/2407.08254v2
These agents can communicate and coordinate with each other, either directly or indirectly, to solve complex tasks that are beyond a single agent’s capabilities

Untitled Document

https://arxiv.org/html/2607.28294v1
This feature fundamentally shapes the asymptotic framework, particularly so when the durations do not have finite expectation

Finite-Time Analysis of Asynchronous Multi-Agent TD Learning

https://arxiv.org/html/2407.20441v1
I Introduction Training reinforcement learning (RL) algorithms is well-known to be a critically time consuming task that can require several data samples to achieve a desired level of accuracy

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

Homogeneous Distributed Observers for Quasilinear Systems

https://arxiv.org/html/2407.05763v1
To the best of the authors’ knowledge, distributed observers for nonlinear systems, which do not satisfy global Lipschitz conditions, are not developed yet