Paper Info
Title
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models
Abstract
This paper describes the participation of the SINAI research group at WASSA 2022 (Empathy and Personality Detection and Emotion Classification). Specifically, we participate in Track 1 (Empathy and Distress predictions) and Track 2 (Emotion classification). We conducted extensive experiments developing different machine learning solutions in line with the state of the art in Natural Language Processing. For Track 1, a Transformer multi-output regression model is proposed. For Track 2, we aim to explore recent techniques based on Zero-Shot Learning models including a Natural Language Inference model and GPT-3, using them in an ensemble manner with a fine-tune RoBERTa model. Our team ranked 2nd in the first track and 3rd in the second track.
Year
DOI
Venue
2022
10.18653/v1/2022.wassa-1.23
PROCEEDINGS OF THE 12TH WORKSHOP ON COMPUTATIONAL APPROACHES TO SUBJECTIVITY, SENTIMENT & SOCIAL MEDIA ANALYSIS
DocType
Volume
Citations 
Conference
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Flor Miriam Del Arco100.34
Jaime Collado-Montañez200.34
Luis Alfonso Ureña López325753.93
María-Teresa Martín-Valdivia400.34