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flightily    
ad. 轻浮地,轻狂地,浮躁地

轻浮地,轻狂地,浮躁地


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  • arXiv. org e-Print archive
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    State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories This restricted form of supervision limits their generality and usability since additional labeled data is needed to specify any other visual concept Learning directly from raw text about images is a promising alternative which leverages a much broader source of supervision We
  • arXiv:1706. 03762v7 [cs. CL] 2 Aug 2023
    arXiv org offers a repository for researchers to share and access academic preprints across diverse scientific fields
  • Submission Overview - arXiv info
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  • High Energy Physics - Theory - arXiv. org
    High Energy Physics - Theory New submissions Cross-lists Replacements See recent articles Showing new listings for Tuesday, 9 June 2026
  • [2501. 12948] DeepSeek-R1: Incentivizing Reasoning Capability in LLMs . . .
    General reasoning represents a long-standing and formidable challenge in artificial intelligence Recent breakthroughs, exemplified by large language models (LLMs) and chain-of-thought prompting, have achieved considerable success on foundational reasoning tasks However, this success is heavily contingent upon extensive human-annotated demonstrations, and models' capabilities are still
  • About arXiv - arXiv info
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  • Artificial Intelligence - arXiv. org
    Artificial Intelligence Authors and titles for recent submissions Thu, 18 Jun 2026 Wed, 17 Jun 2026 Tue, 16 Jun 2026 Mon, 15 Jun 2026 Fri, 12 Jun 2026 See today's new changes
  • [1312. 6114] Auto-Encoding Variational Bayes - arXiv. org
    How can we perform efficient inference and learning in directed probabilistic models, in the presence of continuous latent variables with intractable posterior distributions, and large datasets? We introduce a stochastic variational inference and learning algorithm that scales to large datasets and, under some mild differentiability conditions, even works in the intractable case Our





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