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20222024
most citedEmotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions

9 citations · 12 across the 9 of their papers we have counts for

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cs.CL2024

Compromesso! Italian Many-Shot Jailbreaks Undermine the Safety of Large Language Models

Fabio Pernisi, Dirk Hovy, Paul Röttger

As diverse linguistic communities and users adopt large language models (LLMs), assessing their safety across languages becomes critical. Despite ongoing efforts to make LLMs safe,…

cs.CL2024

Divine LLaMAs: Bias, Stereotypes, Stigmatization, and Emotion Representation of Religion in Large Language Models

Flor Miriam Plaza-del-Arco, Amanda Cercas Curry, Susanna Paoli +2

Emotions play important epistemological and cognitive roles in our lives, revealing our values and guiding our actions. Previous work has shown that LLMs display biases in emotion…

cs.CL20242 cited

Beyond Flesch-Kincaid: Prompt-based Metrics Improve Difficulty Classification of Educational Texts

Donya Rooein, Paul Rottger, Anastassia Shaitarova +1

Using large language models (LLMs) for educational applications like dialogue-based teaching is a hot topic. Effective teaching, however, requires teachers to adapt the difficulty…

cs.CL2024

Conversations as a Source for Teaching Scientific Concepts at Different Education Levels

Donya Rooein, Dirk Hovy

Open conversations are one of the most engaging forms of teaching. However, creating those conversations in educational software is a complex endeavor, especially if we want to add…

cs.CL20249 cited

Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions

Flor Miriam Plaza-del-Arco, Alba Curry, Amanda Cercas Curry +1

Emotions are a central aspect of communication. Consequently, emotion analysis (EA) is a rapidly growing field in natural language processing (NLP). However, there is no consensus…

cs.CL20241 cited

DADIT: A Dataset for Demographic Classification of Italian Twitter Users and a Comparison of Prediction Methods

Lorenzo Lupo, Paul Bose, Mahyar Habibi +2

Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the general public. To facilitate such analyses, we…