AICUP2023-事實文字檢索與查核競賽-後測問卷

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This questionnaire is a small test for participants after the AICUP competition held by IKM lab.

Which of the following statements is NOT true? *

20 points

When preprocessing text data, one often needs to perform text tokenization.

Tokenization can be done in word, character, or even the mix of the two.

Full-width symbol such as punctuation or digits can be convert to half-width one through unicode normalization.

When dealing with Chinese text corpus, one often needs to perform stemming.

What can a claim verification model do? *

20 points

It can translate Chinese documents into English ones.

It can answer human questions.

It can be used for recognizing textual entailment.

It can create arts.

What does it mean to overfit on a claim verification task? *

20 points

It means machine learning models have low accuracies on training set.

It means machine learning models cannot perform well on training set.

It means machine learning models cannot correctly verify claims when given ones are not in the training set.

All of the above.

What does it mean to underfit on a claim verification task? *

20 points

It means machine learning models have low accuracies on training set.

It means machine learning models cannot perform well on training set.

It means machine learning models cannot correctly verify claims when given ones are in the training set.

All of the above.

What are possible solutions to improvements of your claim verification system? *

20 points

Pre-train the model with more data

Improve document or sentence retrieval model

Try different data-processing procedures

All of the above.

Did you get more understanding in natural language processing after this competition?
*

5 (I learned a lot from this competition.)

4 (I learned some new things from this competition.)

3 (I learned a little bit.)

2 (I learned few things.)

1 (I did not learn anything.)

Thank you for joining the AICUP2023 competition! Please leave comments for the competition to help us make improvements.

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