英文 SCI 论文写作常用句式（保持更新）

在这里先推荐一份论文写作指南：Academic Phrasebank，其详细介绍了论文各部分的常用句式，该资料目录如下。

接下来记录本人在阅读论文中总结下来的句式。

摘要部分

引言部分

不失一般性，我们…:

Without loss of generality, we assume that each structured output be represented using d discrete and/or continuous variables.

我们首次展示…虽然这不是我们的主要贡献(对于微小的创新可用):

Therefore, we first show the performance of a neural event extractor on this task, although it is not out main contribution.

通过…实现:

This is supported by the memerships vertically identified between multi-granular events, as well as the horizontal temporal reasoning within the event complex.

贡献在于…:

The second contribution of this work lies in providing a general method for inducing an event complex that comprehensively represents the relational structure of several related event mentions.

赋予…能力:

While previous works focus on preserving logical consistency through post-learning inference or structured learning, there was no effctive way to endow neural models with the sence of global logical consistency during training.

虽然…但是…:

While data-driven methods provide a general and tractable way for event-event relation extraction, their performance is restricted by the limited annotated resources available.

通过…来优化…因为…:

The Probabilistic Inference is employed based on the Gaussian distribution to make the inference robust by taking the possible perturbation of transition scores into account since the perturbation is also learned in a way that coherently explains the uncertainty of the samples.

遭受…影响:

Estimated from the handful of examples, the transition scores may suffer from the statistical uncertainty due to the random fluctuation of scant data.

顾此失彼

Such a framework makes the task easy to conduct but ignores the interaction and correlation between the two subtasks, being susceptible to cascading errors.

在…领域，…问题丞待解决:

In (designing online systems), (trade-off between effectiveness and efficiency) remains a long-standing problem.
(How to build accurate entity tagging systems using less manual effort) is still an open problem.

首次…:

We are the first to employ (a generative pre-trained language model) to address (a few-shot sequence labeling problem).

取而代之:

(Prompt-based learning methods for NLP attempt to circumvent this issue) by instead (learning an LM that models the probability P(x;θ)P(x;\theta)P(x;θ) of text xxx itself and using this probability to predict yyy, reducing or obviating the need for large supervised datasets).

由于…，因此…:

As (some patterns perform possibly much worse than others), (the training set T for our final model may) therefore (contain many mislabeled examples).
The observation that relations and, in particular, event-event relations should be constrained by their logical properties, led to employing global inference to comply with transitivity and symmetry consistency.

在…方面展现优势:

(Our solution enables the learning of the input and the class to interact with each other), which has widely demonstrated it superiority in (modeling the relations of two elements).

等价于…:

(The question that if the input belongs to a class) is equivalent to (ask if the hypothesis is true given the premise)

与其他方法相比…:

(Multiple-Choice QA (MCQA) often requires more advanced reading comprehension skills such as logical reasoning, summarization, and arithmetic operations), compared to (the extractive counterpart where answers are usually spans of text within given passages).
Different from these methods learning the transition scores by optimization, we build a network to generate the transition scores based on the label prototypes instead.

灵感源于…:

(MRC) originally took inspiration from (language proficiency exams).
Our work draws inspiration from Ahn et al.(2016).
Motivated by the logic-driven framework proposed by Li, the declarative logical constraints are converted into differentiable functions that can be incorporated into the learning objective for relation extraction tasks.

已存在大量有关…的研究:

There has been a surge in the amount of research literature on (OpenQA).

扩大…优势的同时，减少…不良影响:

(This method) maximizes (the coverage of important content) while minimizing (redundancy).

多个领域的融合点：

the intersection of (language understanding) and (machine learning).

因…所以无法…:

(this approach) would be using (incomplete information) and could therefore (easily confuse classes especially if there are fine-grained distinctions or portions of the video irrelevant to the action of interest).

从…视角上来看：

(This is challenging ) from a (modeling) perspective as (we have to model variable length videos with a fixed number of parameters).

模型部分

先…再…:

Specifically, we first apply the self-attention mechanism to capture the dependency information between labels and then map the label prototype pairs to the corresponding transition scores.

实验部分

实验表明…有…倾向:

Our preliminary experiments reveal that trigger identification tends to struggle when recognizing triggers of novel event types because novel events usually contain completely different triggers with the semantic distinction from the known events.

领域内常见描述

监督学习/无监督学习/小样本学习

But they almost followed the supervised learning paradigm and depended on the large-scale human-annotated dataset, while new event types emerge every day and most of them suffer from the lack of sufficient annotated data.

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