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30 result(s) for “if com favor site code web de site to raybonecork com site:arxiv.org” of 46 matched · 882 ms

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This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
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Artificial Intelligence

https://arxiv.org/list/cs.AI/new
To bridge this gap, we introduce a novel and comprehensive Interactive SEmantic Enrichment system (ISEE)

Train Often, Deploy Selectively: Forward-Gated Model Replacement in

https://arxiv.org/html/2607.28577v1
org perpetual non-exclusive license arXiv:2607

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
org perpetual non-exclusive license arXiv:2607

General Relativity and Quantum Cosmology

https://arxiv.org/list/gr-qc/new
In continuation to the earlier work (Eur

Report GitHub Issue

https://arxiv.org/html/2608.03077v1
org perpetual non-exclusive license arXiv:2608

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
To address this limitation, we propose Hunyuan3D-Buffalo 1

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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv

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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/src/2405.20232
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https://arxiv.org/src/1910.03771
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https://arxiv.org/pdf/2609.18842
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https://arxiv.org/pdf/2205.11916v2
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https://arxiv.org/pdf/2006.00064
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https://arxiv.org/pdf/2608.03494
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https://arxiv.org/src/2006.00064
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https://arxiv.org/src/2608.04003
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https://arxiv.org/pdf/2309.08431
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https://arxiv.org/src/2212.07841
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https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/src/2006.03206
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https://arxiv.org/pdf/1911.06462
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https://arxiv.org/src/2104.08691
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https://arxiv.org/pdf/2410.05779
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https://arxiv.org/pdf/2608.01934
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https://arxiv.org/pdf/2608.02976
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https://arxiv.org/src/2402.03300
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https://arxiv.org/src/2006.02924
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2506.01844
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsMustafa ShukorDana AubakirovaFrancesco CapuanoPepijn KooijmansSteven PalmaAdil ZouitineMichel AractingiCaroline PascalMartino RussiAndres MarafiotiSimon