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：


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


  • 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
  • Measuring Mathematical Problem Solving With the MATH Dataset
    Abstract: Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers To measure this ability in machine learning models, we introduce MATH, a new dataset of 12,500 challenging competition mathematics problems Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations
  • Weakly-Supervised Affordance Grounding Guided by Part-Level. . .
    In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object interaction images and egocentric
  • Reasoning of Large Language Models over Knowledge Graphs with. . .
    While large language models (LLMs) have made significant progress in processing and reasoning over knowledge graphs, current methods suffer from a high non-retrieval rate This limitation reduces
  • Large Language Models are Human-Level Prompt Engineers
    We propose an algorithm for automatic instruction generation and selection for large language models with human level performance
  • DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION - OpenReview
    Abstract: Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks In this paper we propose a new model architecture DeBERTa (Decoding-enhanced BERT with disentangled attention) that improves the BERT and RoBERTa models using two novel techniques The first is the disentangled attention mechanism, where
  • Faster Cascades via Speculative Decoding | OpenReview
    Cascades and speculative decoding are two common approaches to improving language models' inference efficiency Both approaches interleave two models, but via fundamentally distinct mechanisms:
  • MIND over Body: Adaptive Thinking using Dynamic Computation
    Clever use of intermediate activations to assess input complexity Should be able to work with existing architectures making engineering it for downstream real-world use cases simpler
  • Diffusion Generative Modeling for Spatially Resolved Gene. . .
    Metareview: The paper introduces STEM, a conditional diffusion generative model designed to predict spatial gene expression from histology images, achieving state-of-the-art performance across multiple datasets and evaluation metrics The model effectively captures biological heterogeneity by learning a one-to-many mapping between histology images and spatial transcriptomics data, addressing





中文字典-英文字典  2005-2009