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Emotion Classification
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Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).
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MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs
EmoBench-UA: A Benchmark Dataset for Emotion Detection in Ukrainian
What About Emotions? Guiding Fine-Grained Emotion Extraction from Mobile App Reviews
Emotion Classification In-Context in Spanish
University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection
The Super Emotion Dataset
EmoGist: Efficient In-Context Learning for Visual Emotion Understanding
Interpretable Multi-Task PINN for Emotion Recognition and EDA Prediction
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese Metaphors
MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion Perception
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture
Emo Pillars: Knowledge Distillation to Support Fine-Grained Context-Aware and Context-Less Emotion Classification
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians
Integrating Emotion Distribution Networks and Textual Message Analysis for X User Emotional State Classification
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text
Machine learning based animal emotion classification using audio signals
Symbolic Audio Classification via Modal Decision Tree Learning
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations
Continuous Adversarial Text Representation Learning for Affective Recognition
A novel Fourier Adjacency Transformer for advanced EEG emotion recognition
Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion Classification
VANPY: Voice Analysis Framework
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition
Characteristic-Specific Partial Fine-Tuning for Efficient Emotion and Speaker Adaptation in Codec Language Text-to-Speech Models
Large Vision-Language Models for Knowledge-Grounded Data Annotation of Memes
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
Sentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning
Deep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support Hotlines
EmoNeXt: an Adapted ConvNeXt for Facial Emotion Recognition
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
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