Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers

27 February 2023

Papers citing "Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers"

6 / 6 papers shown

Title
Don't Get Too Excited -- Eliciting Emotions in LLMs Gino Franco Fazzi Julie Skoven Hinge Stefan Heinrich Paolo Burelli 44 0 0 04 Mar 2025
Modeling Story Expectations to Understand Engagement: A Generative Framework Using LLMs Hortense Fong George Gui HAI 91 0 0 13 Dec 2024
MeloTrans: A Text to Symbolic Music Generation Model Following Human Composition Habit Yutian Wang Wanyin Yang Zhenrong Dai Yilong Zhang Kun Zhao Hui Wang 47 2 0 17 Oct 2024
A Computational Analysis of the Dehumanisation of Migrants from Syria and Ukraine in Slovene News Media Jaya Caporusso Damar Hoogland Mojca Brglez Boshko Koloski Matthew Purver Senja Pollak 35 2 0 10 Apr 2024
Fine-grained Affective Processing Capabilities Emerging from Large Language Models Joost Broekens Bernhard Hilpert Suzan Verberne Kim Baraka Patrick Gebhard Aske Plaat AI4MH 46 12 0 04 Sep 2023
$Emotion Embeddings $\unicode{x2014}$ Learning Stable and Homogeneous Abstractions from Heterogeneous Affective Datasets$ Emotion Embeddings $\unicode{x2014}$ Learning Stable and Homogeneous Abstractions from Heterogeneous Affective Datasets Sven Buechel U. Hahn 30 1 0 15 Aug 2023