Crossover: 2014

Chapter 252 Alternative Academic Habits

What does less time mean?

Means an unprecedented increase in efficiency.

Before that, Eve Carly hadn't quite understood how Lin Hui suddenly rose to prominence.

But now she has made up her mind.

But in this case, Eve Carly felt that some of the previous estimates of Lin Hui were a bit conservative.

The training under the same size corpus can save at least 70% of the time compared with the conventional training by introducing the pre-training mechanism based on the migration idea.

This data is quite exaggerated.

If it is as Eve Carly guessed.

What Lin Hui created is not only data exaggeration, but also the functions will be outrageous
It is important to know that things based on migration ideas can be "migrated" in a sense, that is, portability.

This is so outrageous.

Research involving text summarization and even the entire field of natural language processing was more or less self-indulgent.

But if it has mobility, it is entirely possible to penetrate into other fields.

With this in mind, Eve Carly suddenly felt that Lin Hui's focus must not be the small fish pond of natural language processing.

Lin Hui is playing a big game of chess.

Although I have known Lin Hui not long ago, as a person who has frequent academic exchanges with Lin Hui.

Eve Carly can be sure that Lin Hui's academic ambitions are great.

Before that, Eve Carly felt that Lin Hui could open a new door in the direction of natural language processing.

Now it seems that the direction that Lin Hui will influence in the future is definitely not limited to the direction of natural language processing.

When it comes to the entire field of machine learning, Lin Hui will make great achievements.

It may even be far more than that, and Eve Carly is looking forward to it all.

There is nothing more exciting than witnessing the rise of a genius.

(If there is, it may only be witnessing the destruction of a "god".)
Even though Lin Hui doesn't have any title blessings yet.

However, Lin Hui's achievements in the past are already dazzling enough.

Eve Carly believed that Lin Hui would put his ambition into practice little by little.

Why could Eve Carly come to such a judgment?

Lin Hui's brilliant academic achievements in the past are just one of the reasons why Eve Carly came to such an inference.

This is not the most important reason.

What really made Eve Carly realize that Lin Hui can carry out his ambition is that Lin Hui has his own academic style.

Compared to visible academic achievements.

Academic style is very metaphysical, invisible and intangible.

Sounds like something unreal.

But there is such a thing as academic style.

Discussions about the term "academic style" often appear in various academic exchanges and daily discussions among researchers.

Both the academic route and academic habits will affect the formation of academic style in a sense.

To measure whether a scientific researcher is academically competent or above the standard generally depends on whether he has an independent academic style.

In general, scientific researchers who only paddle in the academic field generally do not have their own academic style.

The research results are more arbitrary, and the research topics are mainly "following research".

Researchers above the standard generally have a stable academic style.

The stability of academic style does not mean everything.

But at least it means that the researcher has a relatively clear plan for the academic route.

Maybe Lin Hui himself didn't notice his academic style.

But Eve Carly felt that Lin Hui had his own academic style.

And the style is obvious.

The fact that Lin Hui has an academic style can also reflect the stability of his academic line.

Therefore, Eve Carly believed that Lin Hui could realize her ambition step by step.

And what kind of academic style does Lin Hui have?

Eve Carly, who is too specific, cannot be described accurately for the time being.

But in terms of academic habits, Eve Carly felt that Lin Hui had an extremely distinctive feature.

That is Lin Hui is always committed to winning at the starting line.

Of course, winning at the starting line is just a metaphor, the exact expression should be

——When solving academic problems and practical engineering problems, Lin Hui tends to nip possible problems in the bud.

To come to this judgment, Eve Carly naturally has a corresponding basis.

Take the pre-training that Lin Hui mentioned in the supplementary content of the paper not long ago.

When it comes to "training" before, people often think that the model generated by the training is adjusted by experts in machine learning.

There are very few people like Lin Hui who have ideas about the training process.

After all, when it comes to corpus training, this is already a very advanced issue in language model construction.

In addition to this example, there is also the first conversation with Lin Hui in China this time.

At that time, the two talked about how to deal with the related issues of "the dimension explosion that may be caused by the vectorization of the corpus".

The dimensionality reduction methods originally envisioned by Eve Carly include converting high-dimensional models into low-dimensional models, reducing high-dimensional data obtained after analysis into low-dimensional data, and so on.

However, the idea proposed by Lin Hui is to obtain the original high-dimensional vector data after vectorizing the corpus and directly perform dimension reduction processing.

We must know that few researchers have thought of directly making a fuss about the original data with relatively high dimensions when it comes to the dimension explosion.

After all, this involves abstracting corpus information into vector raw data, which is almost a particularly advanced link in its corresponding research.

Eve Carly felt that these could support her previous judgment.

According to her previous judgment, further inferences can be made on this basis.

If a scientific research project involves multiple links, each link has room for action.

That Lin Hui will definitely focus on the initial stage or open up a new track in the place before the initial stage.

What's the use of knowing this?
Of course it's useful, even great.

Previously, Eve Carly was very unclear about why Lin Hui wanted to acquire the patent she created, namely "A New Method for Text Judgment, Screening and Comparison".

After Lin Hui proposed the generative text summarization algorithm.

The current automatic summarization implementation methods are mainly divided into extractive methods and generative methods:

These two summarization methods have many differences in principle and practical performance.

But both are essentially automatic text summarization.

For example, the technical framework of automatic text summarization can be summarized as follows:

Content representation → weight calculation → content selection → content organization.

Content representation is the process of dividing the original text into text units, mainly preprocessing work such as word segmentation, words, and sentences;

The main purpose of content representation is to process raw text into a form that can be easily analyzed by algorithms through preprocessing.

Weight calculation is to calculate the corresponding weight score for the text unit (that is, the original text after preprocessing). There are various ways to calculate the weight, such as calculating the weight based on feature score, sequence annotation, classification model and other extracted content features.

(End of this chapter)