英文字典中文字典


英文字典中文字典51ZiDian.com



中文字典辞典   英文字典 a   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r   s   t   u   v   w   x   y   z       







请输入英文单字，中文词皆可：

arsis    
n. 强音部,上拍

强音部,上拍

Arsis \Ar"sis\ ([aum]r"s[i^]s), n. [L. arsis, Gr. 'a`rsis a
raising or lifting, an elevation of the voice, fr. a'i`rein
to raise or lift up. Its ordinary use is the result of am
early misapprehension; originally and properly it denotes the
lifting of the hand in beating time, and hence the unaccented
part of the rhythm.]
1. (Pros.)
(a) That part of a foot where the ictus is put, or which
is distinguished from the rest (known as the thesis)
of the foot by a greater stress of voice. --Hermann.
(b) That elevation of voice now called {metrical
accentuation}, or the rhythmic accent.
[1913 Webster]

Note: It is uncertain whether the arsis originally consisted
in a higher musical tone, greater volume, or longer
duration of sound, or in all combined.
[1913 Webster]

2. (Mus.) The elevation of the hand, or that part of the bar
at which it is raised, in beating time; the weak or
unaccented part of the bar; -- opposed to {thesis}.
--Moore.
[1913 Webster]


请选择你想看的字典辞典：
单词字典翻译
arsis查看　arsis　在百度字典中的解释百度英翻中〔查看〕
arsis查看　arsis　在Google字典中的解释Google英翻中〔查看〕
arsis查看　arsis　在Yahoo字典中的解释Yahoo英翻中〔查看〕

安装中文字典英文字典查询工具!


中文字典英文字典工具:
选择颜色:
输入中英文单字

































































英文字典中文字典相关资料:


  • Clever: A Curated Benchmark for Formally Verified Code Generation
    We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean The benchmark comprises of 161 programming problems; it evaluates both formal speci-fication generation and implementation synthesis from natural language, requiring formal correctness proofs for both
  • CLEVER: A Curated Benchmark for Formally Verified Code Generation
    TL;DR: We introduce CLEVER, a hand-curated benchmark for verified code generation in Lean It requires full formal specs and proofs No few-shot method solves all stages, making it a strong testbed for synthesis and formal reasoning
  • The Clever Hans Mirage: A Comprehensive Survey on Spurious. . .
    Back in the early 20th century, a horse named Hans appeared to perform arithmetic and other intellectual tasks during exhibitions in Germany, while it actually relied solely on involuntary cues in
  • Evaluating the Robustness of Neural Networks: An Extreme Value. . .
    Our analysis yields a novel robustness metric called CLEVER, which is short for Cross Lipschitz Extreme Value for nEtwork Robustness The proposed CLEVER score is attack-agnostic and is computationally feasible for large neural networks
  • Contrastive Learning Via Equivariant Representation - OpenReview
    In this paper, we revisit the roles of augmentation strategies and equivariance in improving CL's efficacy We propose CLeVER (Contrastive Learning Via Equivariant Representation), a novel equivariant contrastive learning framework compatible with augmentation strategies of arbitrary complexity for various mainstream CL backbone models
  • Counterfactual Debiasing for Fact Verification
    579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models Unlike existing works, CLEVER is augmentation-free and mitigates biases on infer- ence stage In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information
  • On the Planning Abilities of Large Language Models : A Critical . . .
    While, as we mentioned earlier, there can be thorny “clever hans” issues about humans prompting LLMs, an automated verifier mechanically backprompting the LLM doesn’t suffer from these We tested this setup on a subset of the failed instances in the one-shot natural language prompt configuration using GPT-4, given its larger context window
  • Submissions | OpenReview
    Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers Lorenzo Pacchiardi, Marko Tesic, Lucy G Cheke, Jose Hernandez-Orallo 27 Sept 2024 (modified: 05 Feb 2025) Submitted to ICLR 2025 Readers: Everyone
  • Dual-Model Defense: Safeguarding Diffusion Models from Membership . . .
    Membership inference and memorization is a key challenge with diffusion models Mitigating such vulnerabilities is hence an important topic The idea of using an ensemble of model is clever





中文字典-英文字典  2005-2009