Humor Detection
14 papers with code • 1 benchmarks • 4 datasets
Humor detection is the task of identifying comical or amusing elements.
Benchmarks
These leaderboards are used to track progress in Humor Detection
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Libraries
Use these libraries to find Humor Detection models and implementations
UR-FUNNY
Cards Against Humanity
Latest papers with no code
Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models
Based on the characteristics of the tasks and the strong dialogue-generation capabilities of LLMs, we propose RiC (Reasoning in Conversation), a method that focuses on solving subjective tasks through dialogue simulation.
SOCIALITE-LLAMA: An Instruction-Tuned Model for Social Scientific Tasks
Social science NLP tasks, such as emotion or humor detection, are required to capture the semantics along with the implicit pragmatics from text, often with limited amounts of training data.
From Generalized Laughter to Personalized Chuckles: Unleashing the Power of Data Fusion in Subjective Humor Detection
It seems that concatenating personalized datasets, even with the cost of normalizing the range of annotations across all datasets, if combined with the personalized models, results in an enormous increase in the performance of humor detection.
TextMI: Textualize Multimodal Information for Integrating Non-verbal Cues in Pre-trained Language Models
Our approach, TextMI, significantly reduces model complexity, adds interpretability to the model's decision, and can be applied for a diverse set of tasks while achieving superior (multimodal sarcasm detection) or near SOTA (multimodal sentiment analysis and multimodal humor detection) performance.
The Naughtyformer: A Transformer Understands Offensive Humor
Jokes are intentionally written to be funny, but not all jokes are created the same.
Hybrid Multimodal Fusion for Humor Detection
Our experiments demonstrate the effectiveness of our proposed model and hybrid fusion strategy on multimodal fusion, and the AUC of our proposed model on the test set is 0. 8972.
Don't Take it Personally: Analyzing Gender and Age Differences in Ratings of Online Humor
Computational humor detection systems rarely model the subjectivity of humor responses, or consider alternative reactions to humor - namely offense.
Multimodal Learning using Optimal Transport for Sarcasm and Humor Detection
Multimodal learning is an emerging yet challenging research area.
SemEval 2021 Task 7: HaHackathon, Detecting and Rating Humor and Offense
Our subtasks were binary humor detection, prediction of humor and offense ratings, and a novel controversy task: to predict if the variance in the humor ratings was higher than a specific threshold.
Grenzlinie at SemEval-2021 Task 7: Detecting and Rating Humor and Offense
Detection task is a binary classification task, and the rating prediction task is a regression task between 0 to 5.
