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2 Details of the DVD Dataset M Additional Empirical Application: Fishing-site Choice M
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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

Report GitHub Issue

https://arxiv.org/html/2607.22511v2
× 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 Abstract Download PDF

1 Introduction

https://arxiv.org/html/2608.02854v1
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

Asymptotic Equivalence of Immediate and Deferred Acceptance

https://arxiv.org/html/2607.24970v2
one-to-one random markets, IA’s expected average rank is asymptotically log⁡n\log n, just like DA’s

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

Optimal testing in a class of nonregular models

https://arxiv.org/html/2403.16413v3
org perpetual non-exclusive license arXiv:2403

Nucleosynthesis in Magnetically Driven Jets from Collapsars

https://arxiv.org/html/0804.0969v1
org perpetual non-exclusive license arXiv:0804

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

Can Large Language Models Execute Parent Orders?

https://arxiv.org/html/2607.28410v1
org perpetual non-exclusive license arXiv:2607

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

On the Non-Specificity of Statistical Measures Used in Script

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

Does the Gender Wage Gap Originate at Labor Market Entry? Evidence from

https://arxiv.org/html/2608.03153v1
If large entry-level gaps and substantial selection bias were to show up anywhere, this economy is a plausible place to expect them

1 Introduction

https://arxiv.org/html/2402.03300v3
2 ArXiv Papers Seem Ineffective in Improving Mathematical Reasoning 5

Report GitHub Issue

https://arxiv.org/html/2608.02612v1
org perpetual non-exclusive license arXiv:2608

On the Complexity of Learning to Cooperate with Populations of Socially

https://arxiv.org/html/2407.00419v1
W say that a population of adaptive agents is socially intelligent if its members are (1) individually Hannan-consistent and (2) compatible in the sense that any pair of agents will perform nearly as well as some Pareto-optimal Nash equilibrium of the matrix game

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

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

United We Stand: Decentralized Multi-Agent Planning With Attrition

https://arxiv.org/html/2407.08254v2
We prove that our approach guarantees that the average joint action of all agents converges to a Nash equilibrium (NE) if every agent applies the same RM procedure in any cooperative game with a submodular utility function

1 Introduction

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

Sphere Retraction Normalizations

https://arxiv.org/html/2608.02668v1
com/hazdzz/deep_connection \ncudata[Correspondence]Jie Zhang (), Correspondence: Cheng-Fang Su () “Geometry is not true, it is advantageous

Forthcoming in SIAM Journal on Financial Mathematics Decentralised

https://arxiv.org/html/2309.08431v3
Concentration risk refers to the decrease in fee revenue if the marginal exchange rate (akin to the midprice in a limit order book) in the pool exits the LP’s range of liquidity

1 Introduction

https://arxiv.org/html/2608.03486v1
At the same time, the recent theoretical work of Kolesár and Plagborg-Møller (2025) has demonstrated that statistical identification strategies developed under linearity may fail when the structural relationship between the reduced-form innovations and shocks is nonlinear, even if the shocks themselves satisfy

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

Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
org) Wen Chen is with the Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China(e-mail: wenchen@sjtu

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
begun on July 20, 2026; the present version is dated August 4, 2026. Claude Opus 5 and Fable 5 provided research assistance throughout, spanning code development, data construction and empirical analysis, and the drafting of the manuscript.

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

Decoupling Generation and Selection for Budget-Constrained Faithful

https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license arXiv:2608

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

https://arxiv.org/html/2508.20101v1
Using daily log returns of 50 publicly listed firms over a one-year period, we evaluate the model’s predictive performance in a cross-validation study

Untitled Document

https://arxiv.org/html/2607.28294v1
At the boundary κ=1\kappa=1, where 𝔼​[xi]=∞\mathbb{E}[x_{i}]=\infty, the rate is slower, namely T/log⁡T\sqrt{T/\log T}

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple

https://arxiv.org/html/2608.02966v1
-Choice Benchmarks 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?

Distributed, Parallel, and Cluster Computing

https://arxiv.org/list/cs.DC/new
Several components are the subject of pending United States patent applications by the first author and are presented here as candidate open architectural principles [2] arXiv:2608