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The recorded downgrade reasons in the identification clusters repeatedly report a sound derivation whose content collapses into an existing construction: reviewers describe the delivered result as “generic Manski-style outer containment,� “standard finite response-type sharpness,� “shallow two-point mean
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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

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
A core calculus gives an effect-confinement lemma and six safety properties

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

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

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

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

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

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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

Very Large-Scale Multi-Agent Simulation in AgentScope

https://arxiv.org/html/2407.17789v2
com/modelscope/agentscope/tree/main/examples/paper_large_scale_simulation to inspire further research and development in large-scale multi-agent simulations

Underspecification in Language Modeling Tasks: A Causality-Informed

https://arxiv.org/html/2210.00131v4
Code and open-source demos available at https://github

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

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

AgentScope 1.0: A Developer-Centric Framework for Building Agentic

https://arxiv.org/html/2508.16279v1
org perpetual non-exclusive license arXiv:2508

1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

Machine Learning Dec 2022

https://arxiv.org/list/cs.LG/2022-12
2001-2004 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2212

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

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

Report GitHub Issue

https://arxiv.org/html/2608.03063v1
Our code is available at https://github

1 Introduction

https://arxiv.org/html/2407.02518v2
com Abstract Large language models (LLMs) for code are typically trained to align with natural language instructions to closely follow their intentions and requirements

MinerU2.5: A Decoupled Vision-Language Model for Efficient High

https://arxiv.org/html/2509.22186v2
com/opendatalab/MinerU \metadata[Model:]https://huggingface

1. Introduction

https://arxiv.org/html/2608.02909v1
In practice, most researchers use the generated variables “as is� on the right-hand side of the regression, as if they captured the true, latent variable of interest

Untitled Document

https://arxiv.org/html/2607.28294v1
A second scheme preserves the realized count and sets the number of events in the bootstrap world as n∗=n​(T)n^{\ast}=n(T)

Optimal testing in a class of nonregular models

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

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

Existence of Richter–Peleg representation for general preferences

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

You’ve Got to be Efficient: Ambiguity, Misspecification and

https://arxiv.org/html/2604.05327v4
For these problems, it is therefore always optimal for the decision-maker to proceed as if the likelihood were correctly specified and select the resulting optimal decision rule

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

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

Bandwidth-Free Inference for Recursive Nonlinear Impulse Response

https://arxiv.org/html/2608.02943v1
org perpetual non-exclusive license arXiv:2608

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)