good-paper-sentences-collection
好的句子收集
- Our evaluation shows that our approach obtains better results than task-specific handcrafted representations across different tasks and programming languages (我们的评估结果显示....)
- Leveraging machine learning models for predicting program properties(利用机器学习模型预测程序属性)
- We present a novel program representation (我们提出了一个新的...)
- In this paper, we demonstrate the power and generality of AST paths on the following tasks: (利用下面的任务说明了....)
- Empirical studies have shown that...(实验性的研究表明...)
- Raychev et al. (...等人)i.e. (也就是说) e.g. (比如)
- Automatic generation may produce a prohibitively large number of paths.(产生出令人望而却步的代价...)
- In Sections 3.1 and 3.2 we present CRFs and word2vec(在第几部分我们介绍了...) in this section(这一部分...)
- neural-network based approaches have shown(基于神经网络的方法...)
- we base the following definitions on pairwise paths between AST terminals.(base...on... 基于)
- if and only if...(当且仅当)
- This paper makes the following contributions.(本论文的贡献集中在以下方面)
- Section 6 and 7 are dedicated to the discussion of our results and conclusions.(第6部分和第七部分集中于)
- In the next section we describe(在下一部分我们描述了)
- To summarize, our E.T.-RNN approach would possibly work better than(总的来说.....)
- In this following,(在这之后)
- Khashman tests NN classifiers with different training to validation data ratios (测试了不同训练集和测试集比...)
- By employing different kernel functions, SVM technique can be applied to(通过应用不同的核函数...)
- The process of boosting continues until the loss function reduction becomes limited.(直至损失函数收敛)
- In accordance with the suggestion of Ala’raj and Abbod (2016b),(根据....的建议,不要总是使用according to)
- Ranging from early matrix factorization to recently emerged deep learning based methods,(从早期的矩阵分解,到现在出现的深度学习方法)
- Distinct from HOP-Rec, we contribute a new technique to integrate high-order connectivities into the prediction model,(与......不同,没有用到different from)
- This not only increases the model representation ability, but also boosts the performance for recommendation(提升了性能,使用了boost这个词,而不是improve)
- Towards this end, we perform experiments over user groups of different sparsity levels. (为此,我们开展了实验.....)
- For fair consideration, the latent dimensions of all compared baselines are set the same as in Table 2,(处于公平角度考虑....)
- The results demonstrate the significant superiority of RippleNet over strong baselines(结果展示了模型的明显的提升效果)
- Recently, many studies on extending deep learning approaches for graph data have emerged(最近出现了很多的研究.....)
- Our paper makes notable contributions summarized as follows(我们论文的贡献总结如下:)
- we refer the readers to [39](我们推荐/建议读者参考...)
- Attention mechanisms have become almost a de facto standard in many sequence-based tasks(注意力机制已经成为事实上的标准....)
- In general, the modeling process boils down to extracting local or global connectivity patterns between entities(通常,建模过程归结为....)
- we show marked performance gains in comparison to state-of-the-art methods on all datasets.(和目前最好的结果表现出了显著的结果)
- To the best of our knowledge,(就我们目前所知)
- aroused considerable research interest(引起了很大的研究兴趣)
- we find that COMPGCN outperforms all the existing methods in 4 out of 5 metrics on FB15k-237 and in 3 out of 5 metrics on WN18RR dataset.(数据集里的在4个里面的五个指标上取得了更好的结果)
- We defer this as future work(我们推迟这个作为将来的工作)
- a blowup in the number of parameters that need to be estimated.(大量需要估计的参数)
- Another approach for graph embeddings is thus to leverage proven approaches for language embeddings.(使用已经被证明过的方法...)
- we also discuss quality metrics that provide ways to measure quantitative aspects of these dimensions. (讨论定量的方面....)
- GNNs are notorious for their poor scalability.(GNN因差可扩放性而臭名昭著)
- We speculate that(我们推测...)
- In this setting, we compare the(在这种设置下)
- we leave these results out of our comparison table.(我们在对比结果中排除了....)
- Three benchmark datasets (FB15k-237, WN18RR and FB15k-237-Attr) are utilized in this study. (在本文中使用了...数据集)
- Our work is mainly related to two lines of research(我们的工作主要与两方面的研究有关)
- Empirically, our model yields considerable performance improvements over existing embedding models,(我们的论文取得了很大的效果提升)
- We empirically evaluate different choices of entity representations and relation representations under this framework on the canonical link prediction task(我们在典型的,标准的任务上评估了)
- SEEK can achieve either state-of-the-art or highly competitive performance on a variety of benchmarks for KGE compared with existing methods.(和现在的方法相比,方法达到了有竞争力或者目前最优的解)
- Numerous efforts have since continued to push the boundaries of recurrent language models(人们一直不断努力扩大模型的界限)
- Our overarching interest is whether(我们首要的兴趣是...)
- Our experimental study provides additional evidence for this finding.(我们的实验为之间的发现提供了额外的证明)
- Similar remarks hold for RESCAL and DistMult as well as (albeit to a smaller extent) ConvE and TransE.(类似的说法对于....也成立)
- RESCAL (Nickel et al., 2011), which constitutes one of the first KGE models(Resscal被视作KGE的第一个工作之一)
- predicting the properties of molecules and materials using machine learning (and especially deep learning) is still in its infancy.(使用机器学习预测化学分子或者材料的属性仍然处在初期阶段)
- most research applying machine learning to chemistry tasks has revolved around feature engineering.(大多数的研究都是围绕...)
- empowering HGT to maintain dedicated representation for different types of nodes and edges. (使HGT能够为不同的node和edge获得专门的表示)
- Figure 1 depicts he macro-structure of Mixer.(图1描绘了整体结构)
- Vinyals et al. [32] and Ravi and Larochelle [24] apply Matching Networks using cosine distance. However for both Prototypical Networks and Matching Networks any distance is permissible(对于模型来说...都是允许的)
- For Protypical Networks, we conjecture this is primarily due to cosine distance not being a Bregman divergence(我们猜测某种现象/结果可能是因为...)
- While suggestive as a research result, in terms of practical applications, the zero-shot performance of GPT-2 is still far from use-able.(作为实验结果有启发性)
- We hold that the poor performance of the pre-trained multimodal model may be attributed to the fact that the pre-training datasets and objects have gaps in information extraction tasks. (我们认为/我们假设)
- To steer our models towards appropriate behaviour at a more fine-grained level, we rely heavily on our models themselves as tools.(为了使模型更能够…)