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

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

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Transmission Parameter Allocation in Multi-Gateway LoRa Networks I INTRODUCTION II RELATED WORK III SYSTEM MODEL III-A The Traffic Pattern of LoRa Networks III-B Capture Effect and Quasi-Orthogonality between SFs III-C Packet Delivery

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

https://arxiv.org/html/2608.03452v1
de Abstract When a transformer learns an irregular morphological pattern, what has it learned

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
Project Page: this https URL [2] arXiv:2608

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https://arxiv.org/pdf/2508.11152
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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/pdf/2608.01934
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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/2607.26327v3
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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/2006.02924
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https://arxiv.org/pdf/2006.00342
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Numerical Analysis

https://arxiv.org/list/cs.NA/new
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https://arxiv.org/pdf/2608.02872
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https://arxiv.org/pdf/2608.02694
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