Papers by Khalid Al-Khatib

5 papers
Modeling Deliberative Argumentation Strategies on Wikipedia (P18-1)

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Challenge: Existing models for deliberative discussions have been built manually based on a small set of discussions, resulting in a level of abstraction that is not suitable for move recommendation.
Approach: They propose to model argumentation strategies of deliberative discussions by annotating ongoing discussions with a label that can be used for move description.
Outcome: The proposed model can predict arguments of participants in deliberative discussions using metadata from Wikipedia talk pages.
Unveiling the Power of Argument Arrangement in Online Persuasive Discussions (2023.findings-emnlp)

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Challenge: a recent study shows that the CMV is the best time period in human history for the vast majority of people.
Approach: They extend a semantic argumentation unit type model by clustering type sequences into different argument arrangement patterns and representing discussions as sequences of these patterns.
Outcome: The proposed model outperforms existing classifiers on the change my view forum discussion data.
Indicative Summarization of Long Discussions (2023.emnlp-main)

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Challenge: Using large language models, we generate indicative summaries instead of informative summary for long discussions.
Approach: They propose an unsupervised approach to generating indicative summaries using large language models using large-scale language models.
Outcome: The proposed method clusters argument sentences, generates abstractive summaries, and classifies the generated cluster labels into argumentation frames.
Citance-Contextualized Summarization of Scientific Papers (2023.findings-emnlp)

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Challenge: Current automatic summarization approaches generate abstracts, but abstracts do not show relationship between paper and references.
Approach: They propose a contextualized summarization approach that generates an informative summary . they extract and model the citances of a paper, retrieve relevant passages from cited papers, and generate abstractive summaries tailored to each citance.
Outcome: The proposed method extracts and models the citances of a paper, retrieves relevant passages from cited papers, and generates abstractive summaries tailored to each citance.
Argumentation Synthesis following Rhetorical Strategies (C18-1)

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Challenge: Existing argument mining studies focus on logical structure of arguments, identifying their units and relations, and the effects of logical and emotional arguments across audiences.
Approach: They propose to use rhetorical strategies to synthesize argumentative texts with different strategies.
Outcome: The proposed model shows that the experts agree significantly more on selection when following the same strategy.

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