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You’ve Got to be Efficient: Ambiguity, Misspecification and

https://arxiv.org/html/2604.05327v4
Variational Preferences 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?

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
The total number of recommendations is 517 across 471 empirical papers, 321 of which have at least one recommendation

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
CV) Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing

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https://arxiv.org/src/2211.01910v2
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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2608.01785
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MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
Learning-based methods have become increasingly effective for solving co (co) problems, especially vrp (vrp)-related variants

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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/pdf/2205.01882v5
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\dotsttsfontdots.tts.edit: Precisely Controlled Speech Editing with a

https://arxiv.org/html/2608.02673v1
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https://arxiv.org/html/2506.01844v1
A prominent example of this trend are large language models (LLMs), which have demonstrated performance comparable to the average human in understanding and generating natural language, reasoning over complex topics, and anchoring in knowledge (Brown et al

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https://arxiv.org/pdf/2608.03898
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https://arxiv.org/src/2006.03720
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https://arxiv.org/src/2608.03994
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https://arxiv.org/src/2006.01128
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https://arxiv.org/src/2006.00064
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https://arxiv.org/pdf/2608.02976
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https://arxiv.org/src/2006.02759
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https://arxiv.org/src/2608.03883
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https://arxiv.org/pdf/2006.02602
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https://arxiv.org/src/2006.01048
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https://arxiv.org/src/2006.01331
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https://arxiv.org/pdf/2608.02666
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https://arxiv.org/src/2104.08691
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2006.01128
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https://arxiv.org/src/2006.02085
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