Papers by Farjana Sultana Mim

4 papers
Unsupervised Learning of Discourse-Aware Text Representation for Essay Scoring (P19-2)

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Challenge: Existing document embedding approaches focus on capturing sequences of words in documents . however, some document classification and regression tasks need to consider discourse structure of text .
Approach: They propose an unsupervised approach to capture discourse structure in terms of coherence and cohesion for document embedding that does not require expensive parsers or annotation.
Outcome: The proposed method improves essay Organization scoring and Argument Strength scoring.
IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments (2022.lrec-1)

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Challenge: Using crowdsourcing, we show that models trained with domain-specific implicit reasonings outperform domain-general models in both automatic and human evaluations.
Approach: They propose to create a domain-specific corpus of implicit reasonings annotated for a wide range of arguments and use it to generate models.
Outcome: The proposed corpus outperforms domain-general models in automatic and human evaluations.
LPAttack: A Feasible Annotation Scheme for Capturing Logic Pattern of Attacks in Arguments (2022.lrec-1)

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Challenge: Argumentation plays a central role in human communication, where refuting or attacking others’ arguments is a common persuasion strategy.
Approach: They propose a novel annotation scheme that captures common modes and complex rhetorical moves in attacks along with the implicit presuppositions and value judgments.
Outcome: The proposed scheme shows moderate agreement between the two annotations, indicating that human annotation is feasible.
TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation (2022.lrec-1)

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Challenge: Argumentation and debate are effective tools for developing critical thinking skills, but it requires a lot of time and effort.
Approach: They propose to automate the process of giving diagnostic comments to students . they define criteria for a template set that can be used to evaluate the model .
Outcome: The proposed model can be used to evaluate arguments and evaluate them in real time.

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