SOTAVerified

Sarcasm Detection

The goal of Sarcasm Detection is to determine whether a sentence is sarcastic or non-sarcastic. Sarcasm is a type of phenomenon with specific perlocutionary effects on the hearer, such as to break their pattern of expectation. Consequently, correct understanding of sarcasm often requires a deep understanding of multiple sources of information, including the utterance, the conversational context, and, frequently some real world facts.

Source: Attentional Multi-Reading Sarcasm Detection

Papers

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Showing 1–50 of 266 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
DIP: Dual Incongruity Perceiving Network for Sarcasm DetectionCode1
RCLMuFN: Relational Context Learning and Multiplex Fusion Network for Multimodal Sarcasm DetectionCode1
Multi-modal Sarcasm Detection and Humor Classification in Code-mixed ConversationsCode1
"Did you really mean what you said?" : Sarcasm Detection in Hindi-English Code-Mixed Data using Bilingual Word EmbeddingsCode1
News Headlines Dataset For Sarcasm DetectionCode1
InterCLIP-MEP: Interactive CLIP and Memory-Enhanced Predictor for Multi-modal Sarcasm DetectionCode1
Perceived and Intended Sarcasm Detection with Graph Attention NetworksCode1
UTNLP at SemEval-2022 Task 6: A Comparative Analysis of Sarcasm Detection Using Generative-based and Mutation-based Data AugmentationCode1
CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal ModelsCode1
Multi-Modal Sarcasm Detection Based on Contrastive Attention MechanismCode1
Dual-level Adaptive Incongruity-enhanced Model for Multimodal Sarcasm DetectionCode1
A Multimodal Corpus for Emotion Recognition in SarcasmCode1
“Did you really mean what you said?” : Sarcasm Detection in Hindi-English Code-Mixed Data using Bilingual Word EmbeddingsCode1
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction ExpertsCode1
Modelling Context with User Embeddings for Sarcasm Detection in Social MediaCode1
Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional NetworkCode1
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text ClassificationCode1
Sarcasm Detection using Hybrid Neural NetworkCode1
Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge EnhancementCode1
When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party DialoguesCode1
SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and ArabicCode1
Reactive Supervision: A New Method for Collecting Sarcasm DataCode1
Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in ArabicCode1
The Role of Conversation Context for Sarcasm Detection in Online InteractionsCode1
MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection SystemCode1
Affective and Contextual Embedding for Sarcasm DetectionCode1
A Survey on Automated Sarcasm Detection on Twitter—0
A Survey of Multimodal Sarcasm Detection—0
Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling—0
Assessing how hyperparameters impact Large Language Models' sarcasm detection performance—0
ArSarcasm Shared Task: An Ensemble BERT Model for SarcasmDetection in Arabic Tweets—0
AMOA: Global Acoustic Feature Enhanced Modal-Order-Aware Network for Multimodal Sentiment Analysis—0
Cross-lingual Flames Detection in News Discussions—0
Are Word Embedding-based Features Useful for Sarcasm Detection?—0
A Report on the 2020 Sarcasm Detection Shared Task—0
All-in-One: A Deep Attentive Multi-task Learning Framework for Humour, Sarcasm, Offensive, Motivation, and Sentiment on Memes—0
connotation_clashers at SemEval-2022 Task 6: The effect of sentiment analysis on sarcasm detection—0
A Comprehensive Analysis of Preprocessing for Word Representation Learning in Affective Tasks—0
Context-Aware Sarcasm Detection Using BERT—0
Cross-Cultural Transfer Learning for Text Classification—0
CrystalNest at SemEval-2017 Task 4: Using Sarcasm Detection for Enhancing Sentiment Classification and Quantification—0
Bootstrapped Learning of Emotion Hashtags \#hashtags4you—0
BNS-Net: A Dual-channel Sarcasm Detection Method Considering Behavior-level and Sentence-level Conflicts—0
A Novel Hierarchical BERT Architecture for Sarcasm Detection—0
Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection—0
Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data—0
AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset—0
An LSTM-Based Deep Learning Approach for Detecting Self-Deprecating Sarcasm in Textual Data—0
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All datasetsBIG-bench (SNARKS)FigLang 2020 Reddit DatasetFigLang 2020 Twitter DatasetSARC (all-bal)SARC (pol-bal)iSarcasmMUStARDSARC (pol-unbal)WITS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PaLM 2(few-shot, k=3, CoT)Accuracy84.8—Unverified
2PaLM 2 (few-shot, k=3, Direct)Accuracy78.7—Unverified
3PaLM 540B (few-shot, k=3)Accuracy78.1—Unverified
4BLOOM 176B (few-shot, k=3)Accuracy72.47—Unverified
5Bloomberg GPT (few-shot, k=3)Accuracy69.66—Unverified
6GPT-NeoX (few-shot, k=3)Accuracy62.36—Unverified
7Chinchilla-70B (few-shot, k=5)Accuracy58.6—Unverified
8Gopher-280B (few-shot, k=5)Accuracy48.3—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT+Aspect-based approachesF10.74—Unverified
2RoBERTa_large - (Separated Context-Response)F10.72—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa_large (Context-Response)F10.77—Unverified
2BERTF10.73—Unverified
#ModelMetricClaimedVerifiedStatus
1CASCADEAccuracy77—Unverified
2Bag-of-BigramsAccuracy75.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Bag-of-BigramsAccuracy76.5—Unverified
2CASCADEAccuracy74—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa + Mutation Data AugmentationF1-Score0.41—Unverified
#ModelMetricClaimedVerifiedStatus
1MUStARD++Precision70.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Bag-of-WordsAvg F127—Unverified
#ModelMetricClaimedVerifiedStatus
1BARTR136.88—Unverified