Papers by Iza Škrjanec

3 papers
Script Parsing with Hierarchical Sequence Modelling (2021.starsem-1)

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Challenge: Script knowledge is a category of commonsense knowledge that describes how people conduct everyday activities sequentially.
Approach: They propose a hierarchical sequence model and transfer learning to do script parsing with a sequence model that accurately tags script participants.
Outcome: The proposed model improves state of the art of event parsing by over 16 points F-score and, for the first time, accurately tags script participants.
Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the “right reasons”? (2024.acl-long)

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Challenge: a wide body of evidence shows that human language processing difficulty is predicted by the information-theoretic measure surprisal, a word’s negative log probability in context.
Approach: They propose to use large language models to predict the surprisal of a word's negative log probability in context to test their predictive power.
Outcome: The proposed model can be significantly more accurate than humans because it has more data.
Barch: an English Dataset of Bar Chart Summaries (2022.lrec-1)

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Challenge: a new dataset of human-written summaries of bar charts is available in english . a chart summary is a textual description of a data point, which is often analytical .
Approach: They propose a dataset of human-written summaries describing bar charts in english . a total of 47 charts are presented in the dataset, which includes 47 charts .
Outcome: a new dataset of human-written summaries describing bar charts is presented in english . the dataset shows that human speakers often include such statements into chart summary .

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