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These observations establish that the gas-water interface of microbubbles is not the site for hydroxyl radical generation (else CL would be recorded in all cases)
from the top result below

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

Artificial Intelligence

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

Cryptography and Security

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

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

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 system distinguishes two layers of trust: the kernel establishes proof soundness; the statement audit checks whether the formal statement matches the intended claim

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
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)

Untitled Document

https://arxiv.org/html/2607.28294v1
6 Bootstrap law of large numbers License: CC BY-NC-ND 4

Bandwidth-Free Inference for Recursive Nonlinear Impulse Response

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

1 Introduction

https://arxiv.org/html/2407.15077v2
Although HAPPO introduces the first multi-agent trust region method that enjoys a theoretically justified monotonic improvement guarantee, it results in poor performance due to the lack of a theoretical guarantee for individual policy improvement

Computational Geometry

https://arxiv.org/list/cs.CG/new
PR) The Johnson--Lindenstrauss lemma asserts that every set of $n$ points in $d$-dimensional Euclidean space embeds into $O(\varepsilon^{-2}\log n)$-dimensional Euclidean space with distortion at most $1+\varepsilon$

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

Systems and Control

https://arxiv.org/list/cs.SY/new
more | all New submissions (showing 8 of 8 entries) [1] arXiv:2608

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

https://arxiv.org/html/2608.03452v1
Probing five architectures, twelve trained models each, under lemma-disjoint cross-validation with controls and surface baselines, we show that the models encode the L-shaped class itself, not just its visible alternations

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license arXiv:2608

Effort-Centric Fairness in Lending Decisions

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

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

Information Theory

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

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

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

https://arxiv.org/html/2508.20101v1
However, in real-world financial systems, individual assets are not isolated

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

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

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
This version: I would like to thank Xu Cheng, Frank Diebold, Wayne Gao, George Mailath, and seminar participants at Chicago Booth, Paris Econometrics Seminar, Toulouse School of Economics, and the University of Pennsylvania for valuable discussions and comments that substantially improved this article

Finite-Time Analysis of Asynchronous Multi-Agent TD Learning

https://arxiv.org/html/2407.20441v1
However, in real-world multi-agent systems, inter-node communication imposes strong constraints, such as limited link capacity and transmission delays [4, 5, 6]

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

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

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

https://arxiv.org/html/2407.04974v1
This attribute enhances its convenience and practicality for real-world applications