Papers by Ines Reinig

4 papers
ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications (2024.naacl-long)

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Challenge: Existing statistical phrasal or hierarchical machine translation systems relies on a large set of translation rules which results in engineering challenges.
Approach: They propose to use factorized grammar from the field of linguistics as more general translation rules from XTAG English Grammar to generate a manually crafted summarization dataset.
Outcome: The proposed method outperforms existing methods on low-resource language translation tasks with less training data.
How to Do Politics with Words: Investigating Speech Acts in Parliamentary Debates (2024.lrec-main)

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Challenge: a new perspective on framing through the lens of speech acts investigates how politicians make use of different pragmatic speech act functions in political debates.
Approach: They propose a new framework for framing through the lens of speech acts and an annotation scheme for political debates.
Outcome: The proposed framework can predict speech acts with an avg. F1 of around 82.0% . the proposed framework is based on a dataset of German parliamentary debates .
Moral Framing in Politics (MFiP): A new resource and models for moral framing (2025.emnlp-main)

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Challenge: Recent studies have focused on detecting moral values in political communication, trying to identify moral frames used by political actors or parties to convey their messages.
Approach: They propose to code German parliamentary debates to identify moral framing and to detect subtle differences in politicians’ moral framming.
Outcome: The proposed model distinguishes between different types of moral frames and includes narrative roles, together with the moral foundations for each frame.
A Survey on Modelling Morality for Text Analysis (2024.findings-acl)

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Challenge: Recent work on modelling morality in text has garnered increasing attention due to its complexity and complexity.
Approach: They provide a systematic review of recent work on modelling morality in text . they discuss challenges and research gaps in the area of NLP .
Outcome: The authors present their work on the modelling of morality in text, which has garnered increasing attention in recent years.

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