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 51100 of 458 papers

TitleStatusHype
NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion AnalysisCode0
NTUA-SLP at IEST 2018: Ensemble of Neural Transfer Methods for Implicit Emotion ClassificationCode0
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-TrainingCode0
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNNCode0
Multitask Learning for Emotionally Analyzing Sexual Abuse DisclosuresCode0
MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMsCode0
PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in ConversationsCode0
Minimax Filter: Learning to Preserve Privacy from Inference AttacksCode0
Cross-lingual Emotion Intensity PredictionCode0
Multimodal Speech Emotion Recognition Using Audio and TextCode0
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion RegressionCode0
Large Vision-Language Models for Knowledge-Grounded Data Annotation of MemesCode0
A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG DataCode0
KAM -- a Kernel Attention Module for Emotion Classification with EEG DataCode0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Improved acoustic-to-articulatory inversion using representations from pretrained self-supervised learning modelsCode0
Inducing a Lexicon of Abusive Words – a Feature-Based ApproachCode0
Leaving Some Facial Features BehindCode0
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair AnalysisCode0
IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word RepresentationsCode0
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
Extending Adversarial Attacks to Produce Adversarial Class Probability DistributionsCode0
Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional NetworkCode0
Impact of time and note duration tokenizations on deep learning symbolic music modelingCode0
Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion ClassificationCode0
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational AgentsCode0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
EmoTxt: A Toolkit for Emotion Recognition from TextCode0
Emotion Transfer Using Vector-Valued Infinite Task LearningCode0
Enhancing Cognitive Models of Emotions with Representation LearningCode0
Context-Aware Emotion Recognition NetworksCode0
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classificationCode0
Classifying and Visualizing Emotions with Emotional DANCode0
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution NetworksCode0
Emotion Classification in German Plays with Transformer-based Language Models Pretrained on Historical and Contemporary LanguageCode0
Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music DatasetCode0
Speech Emotion Recognition Using Multi-hop Attention MechanismCode0
Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss FunctionCode0
Investigating Emotion-Color Association in Deep Neural NetworksCode0
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian TextsCode0
Emotion Action Detection and Emotion Inference: the Task and DatasetCode0
Is Style All You Need? Dependencies Between Emotion and GST-based Speaker RecognitionCode0
ArmanEmo: A Persian Dataset for Text-based Emotion DetectionCode0
Emotion Recognition from SpeechCode0
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural AnnotatorsCode0
Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in VideosCode0
BYEL : Bootstrap Your Emotion LatentCode0
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese MetaphorsCode0
An Ensemble Approach to Detect Emotions at an Essay LevelCode0
BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion ClassificationCode0
Show:102550
← PrevPage 2 of 10Next →

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