Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts

6 papers
Mining, Assessing, and Improving Arguments in NLP and the Social Sciences (2023.eacl-tutorials)

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Challenge: a tutorial on argument quality assessment will focus on what makes an argument good or bad . argument quality is a field encompassing varying tasks on the automated analysis and synthesis of natural language arguments.
Approach: This tutorial will focus on the assessment of argument quality across disciplines . authors will involve participants in annotation studies on the quality assessment .
Outcome: The tutorial will focus on the assessment of argument quality across disciplines . it will involve participants in two annotation studies on the quality assessment and the improvement of quality .
Emotion Analysis from Texts (2023.eacl-tutorials)

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Challenge: Emotion analysis in text is a field of research that encompasses a set of various natural language processing tasks.
Approach: This tutorial provides an overview of research from emotion psychology . it discusses the use cases of emotion analysis in text, their societal impact and ethical considerations .
Outcome: This paper provides an overview of research from emotion psychology which sets the ground for choosing adequate NLP methodology.
Summarization of Dialogues and Conversations At Scale (2023.eacl-tutorials)

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Challenge: Conversations are the natural communication format for people.
Approach: This tutorial will survey the cutting-edge methods for summarizing written and spoken conversation.
Outcome: This tutorial will examine the cutting-edge methods for summarizing written and spoken conversations, covering key sub-areas whose combination is needed for a successful solution.
Understanding Ethics in NLP Authoring and Reviewing (2023.eacl-tutorials)

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Challenge: This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues .
Approach: This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . the methodology is interactive and participatory, including case studies and working in groups .
Outcome: This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . the methodology is interactive and participatory, including case studies and working in groups.
AutoML for NLP (2023.eacl-tutorials)

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Challenge: Automated Machine Learning (AutoML) is an emerging field that has potential to impact how we build models in NLP.
Approach: This tutorial will summarize the main AutoML techniques and illustrate how to apply them to improve the NLP model-building process.
Outcome: This tutorial summarizes the main AutoML techniques and illustrates how to apply them to improve the model-building process.
Privacy-Preserving Natural Language Processing (2023.eacl-tutorials)

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Challenge: This tutorial will help the NLP community to get familiar with current research in privacy-preserving methods.
Approach: This tutorial will help the NLP community to get familiar with current research in privacy-preserving methods.
Outcome: The tutorial will cover membership inference, differential privacy, homomorphic encryption, or federated learning, all with typical use-cases and potential pitfalls.

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