SOTAVerified

Humor Detection

Humor detection is the task of identifying comical or amusing elements.

Papers

Showing 110 of 64 papers

TitleStatusHype
XGBoost: A Scalable Tree Boosting SystemCode4
XLNet: Generalized Autoregressive Pretraining for Language UnderstandingCode1
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment AnalysisCode1
SynthesizRR: Generating Diverse Datasets with Retrieval AugmentationCode1
ColBERT: Using BERT Sentence Embedding in Parallel Neural Networks for Computational HumorCode1
The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and StressCode1
Humor Detection: A Transformer Gets the Last LaughCode1
MemeCLIP: Leveraging CLIP Representations for Multimodal Meme ClassificationCode1
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction ExpertsCode1
A Sentiment and Emotion Aware Multimodal Multiparty Humor Recognition in Multilingual Conversational Setting0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ColBERT modelF1-score0.98Unverified
2XLNet Large CasedF1-score0.92Unverified
3Multinomial NBF1-score0.88Unverified
4SVMF1-score0.87Unverified
5XGBoostF1-score0.81Unverified
6Decision TreeF1-score0.79Unverified