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However, their rigid dataset-specific adaptation inherently restricts cross-site generalization
from the top result below
https://arxiv.org/list/cs.CV/new
Project Page: this https URL
[2] arXiv:2608
https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts
https://arxiv.org/html/2608.02613v1
A million-token cloud context window does not help here, as it requires off-device upload, which privacy-sensitive personal memory management is meant to avoid
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
https://arxiv.org/html/2609.03371v1
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https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license
arXiv:2607
https://arxiv.org/list/econ/new
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New submissions (showing 21 of 21 entries)
[1] arXiv:2608
https://arxiv.org/html/2608.02817v1
Reviving Micro Real Rigidities: The Importance of Demand ShocksThe views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System
https://arxiv.org/list/math/new
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New submissions (showing 219 of 219 entries)
[1] arXiv:2608
https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries
https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/html/2608.02612v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.01785
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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
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
https://arxiv.org/html/2508.20101v1
In an empirical application, we demonstrate how the model can be applied to financial stock networks
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/2608.00648v1
The framework is suitable for a broad range of distributed task-planning applications and can be flexibly transferred to related scenarios with different practical constraints and settings
https://arxiv.org/abs/2608.12700
A kernel can pass that test and still be silently wrong
https://arxiv.org/abs/2204.04218
In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques capture several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results
https://arxiv.org/list/cs.DB/new
We propose an architectural pattern for such systems, a trusted kernel with a generative shell, resting on one invariant: a component that can fabricate may influence which question the system answers, never which value it returns
https://arxiv.org/list/cs.OS/new
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New submissions (showing 2 of 2 entries)
[1] arXiv:2608
https://arxiv.org/abs/2608.01651
We present Bole, a kernel--runtime co-design that enables efficient tree speculation for hybrid-attention LLMs
https://arxiv.org/list/cs.LG/2022-12
2001-2004
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[1] arXiv:2212
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/2511.06451v1
Spectral safety and discrete Green kernel
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
https://arxiv.org/list/quant-ph/new
Here, we establish a curvature--gauge framework in which the geometry of an embedded manifold functions as a tunable control field for classical trajectories and quantum states