SOTAVerified

Emotion Classification

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).

Papers

Showing 5175 of 458 papers

TitleStatusHype
Interpretable Multi-Task PINN for Emotion Recognition and EDA Prediction0
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese MetaphorsCode0
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture0
Emo Pillars: Knowledge Distillation to Support Fine-Grained Context-Aware and Context-Less Emotion Classification0
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians0
Integrating Emotion Distribution Networks and Textual Message Analysis for X User Emotional State Classification0
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG0
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations0
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text0
Machine learning based animal emotion classification using audio signals0
Symbolic Audio Classification via Modal Decision Tree Learning0
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations0
Continuous Adversarial Text Representation Learning for Affective Recognition0
Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion ClassificationCode0
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions0
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition0
Characteristic-Specific Partial Fine-Tuning for Efficient Emotion and Speaker Adaptation in Codec Language Text-to-Speech Models0
Large Vision-Language Models for Knowledge-Grounded Data Annotation of MemesCode0
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition0
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair AnalysisCode0
Sentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning0
Deep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support HotlinesCode0
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding0
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63Unverified
2MARLIN (ViT-B)Accuracy80.6Unverified
3MARLIN (ViT-S)Accuracy80.38Unverified
4ConCluGenAccuracy66.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6Unverified
2BERT+DKAccuracy0.59Unverified
3BERT-GCNAccuracy0.59Unverified
4Transformer (finetune)Macro-F10.56Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4Unverified
2STEP [bhattacharya2019step]Accuracy78.24Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34Unverified
2CC - XGBF-F1 score (Comb.)0.33Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88Unverified
2NPN + Explanation TrainingF130.29Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71Unverified