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https://arxiv.org/html/2607.29442v2
That is, does there exist a tick-by-tick model, replicating the salient features of ultrahigh-frequency prices, whose scaling limit is of the form Yt=Xt+ZtY_{t}=X_{t}+Z_{t} with ZZ a continuous-time rough process
https://arxiv.org/html/2504.19413v1
2 Proposed Methods
2.1 Mem0
2.2 Mem0gsuperscriptMem0𝑔\texttt{Mem0}^{\tiny g}Mem0 start_POSTSUPERSCRIPT italic_g end_POSTSUPERSCRIPT
3 Experimental Setup
3.1 Dataset
3.2 Evaluation Metrics
(1) Performance Metrics
(2) Deployment Metrics
https://arxiv.org/list/nucl-th/new
03022 [pdf, other]
Title: Does strange meson condensation reduce the moment of inertia of massive proto neutron stars
https://arxiv.org/list/hep-ph/new
A smooth log-linear trend is given a conditional renormalization-group motivation through dimensional transmutation in a hypothetical asymptotically free confining sector; this motivates, but does not microscopically derive, the mass formula
https://arxiv.org/html/2608.03610v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03077v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2608.02854v1
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https://arxiv.org/list/astro-ph.SR/new
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New submissions (showing 19 of 19 entries)
[1] arXiv:2608
https://arxiv.org/html/2608.03411v1
com
Abstract
Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics often fail to capture the model’s true epistemic state
https://arxiv.org/html/2607.26405v1
& Optimal Design
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https://arxiv.org/html/2412.12213v2
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https://arxiv.org/html/2608.03038v1
Consequently, many published evaluations examine models that have since been superseded
https://arxiv.org/html/2407.06328v2
By employing task allocation games – dynamic extensions of conventional population games – we examine how errors in payoff estimation by individual agents affect the convergence of the strategy revision process
https://arxiv.org/list/eess.IV/new
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New submissions (showing 9 of 9 entries)
[1] arXiv:2608
https://arxiv.org/html/2407.03956v3
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https://arxiv.org/html/2508.20105v2
Turbulence
A Introduction
A.1 Stock Market and Turbulence
A.2 Market dynamics and Computational Approach
B Research Gap
C Research objective
D Proposition
E Research Methods
E.1 Tools and Techniques
E.2 Extended Fourier Transform
E.3
https://arxiv.org/html/2407.20004v1
our cities
Road Networks.
Traffic simulator.
Navigation services APIs.
Modified fastest route.
GPS Data.
Data and Code availability.
Acknowledgements.
Author contributions
Corresponding authors
A Supplementary Figures
B Supplementary
https://arxiv.org/list/gr-qc/new
We examine the energy conditions-namely, null, weak, strong, and dominant energy conditions and explore how topological charge influences or controls these conditions
https://arxiv.org/html/2407.08254v2
1 Introduction
2 Related Work
3 Problem Formulation
3.1 Multi-agent planning with attrition
4 Attritable MCTS with Regret Minimization
4.1 Overview of the A-MCTS algorithm
4.2 Regret Matching For Cooperative Coordination
4.3 Analysis and
https://arxiv.org/list/eess/new
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https://arxiv.org/pdf/2608.03898
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https://arxiv.org/src/2608.03994
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https://arxiv.org/src/2006.03720
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https://arxiv.org/pdf/2608.02976
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https://arxiv.org/src/2006.00064
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https://arxiv.org/src/2006.01128
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