Papers Humor Detection
“Humor Detection” 태그가 달린 논문 70편 · 필터 해제
CaRGo-T: Causal Reasoning Graph-of-Thought improves Multimodal Humor Comprehension
Large-scale vision-language models (VLMs) have demonstrated remarkable versatility across a wide range of multimodal tasks. However, understanding humor remains challenging because humorous content often depends on subtl…
Humor DetectionBeyond a Joke: Multi-Angle Reasoning for Detecting and Explaining Harmful Humor in Memes
Internet memes intertwine visual cues, textual content, and cultural context, making them particularly challenging to interpret in scenarios where humor, sarcasm, and harmful intent coexist. These complexities highlight …
Humor DetectionMixSarc: A Bangla-English Code-Mixed Corpus for Implicit Meaning Identification
Bangla-English code-mixing is widespread across South Asian social media, yet resources for implicit meaning identification in this setting remain scarce. Existing sentiment and sarcasm models largely focus on monolingua…
Humor DetectionGRCF: Two-Stage Groupwise Ranking and Calibration Framework for Multimodal Sentiment Analysis
Most Multimodal Sentiment Analysis research has focused on point-wise regression. While straightforward, this approach is sensitive to label noise and neglects whether one sample is more positive than another, resulting …
Multimodal Sentiment AnalysisSarcasm DetectionHumor DetectionDark & Stormy: Modeling Humor in Sentences from the Bulwer-Lytton Fiction Contest
Textual humor is enormously diverse and computational studies need to account for this range, including intentionally bad humor. In this paper, we curate and analyze a novel corpus of sentences from the Bulwer-Lytton Fic…
Humor DetectionTowards Minimal Causal Representations for Human Multimodal Language Understanding
Human Multimodal Language Understanding (MLU) aims to infer human intentions by integrating related cues from heterogeneous modalities. Existing works predominantly follow a ``learning to attend" paradigm, which maximize…
Multimodal Sentiment AnalysisSarcasm DetectionHumor DetectionStandUp4AI: A New Multilingual Dataset for Humor Detection in Stand-up Comedy Videos
Aiming towards improving current computational models of humor detection, we propose a new multimodal dataset of stand-up comedies, in seven languages: English, French, Spanish, Italian, Portuguese, Hungarian and Czech. …
Humor Detectionspeech-recognitionSpeech RecognitionDeceptive Humor: A Synthetic Multilingual Benchmark Dataset for Bridging Fabricated Claims with Humorous Content
This paper presents the Deceptive Humor Dataset (DHD), a novel resource for studying humor derived from fabricated claims and misinformation. In an era of rampant misinformation, understanding how humor intertwines with …
Humor DetectionMisinformationMemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification
The complexity of text-embedded images presents a formidable challenge in machine learning given the need for multimodal understanding of multiple aspects of expression conveyed by them. While previous research in multim…
ClassificationHateful Meme ClassificationHumor DetectionMeme ClassificationTHInC: A Theory-Driven Framework for Computational Humor Detection
Humor is a fundamental aspect of human communication and cognition, as it plays a crucial role in social engagement. Although theories about humor have evolved over centuries, there is still no agreement on a single, com…
Humor DetectionLOLgorithm: Integrating Semantic,Syntactic and Contextual Elements for Humor Classification
This paper explores humor detection through a linguistic lens, prioritizing syntactic, semantic, and contextual features over computational methods in Natural Language Processing. We categorize features into syntactic, s…
Feature EngineeringHumor DetectionSentenceAVR: Synergizing Foundation Models for Audio-Visual Humor Detection
In this work, we present, AVR application for audio-visual humor detection. While humor detection has traditionally centered around textual analysis, recent advancements have spotlighted multimodal approaches. However, t…
Humor DetectionThe MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition
The Multimodal Sentiment Analysis Challenge (MuSe) 2024 addresses two contemporary multimodal affect and sentiment analysis problems: In the Social Perception Sub-Challenge (MuSe-Perception), participants will predict 16…
Humor DetectionMultimodal Sentiment AnalysisSentiment AnalysisSynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
It is often desirable to distill the capabilities of large language models (LLMs) into smaller student models due to compute and memory constraints. One way to do this for classification tasks is via dataset synthesis, w…
Bias DetectionDiversityHumor DetectionInformation Retrieval+6Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models
Large Language Models (LLMs) have achieved remarkable performance in objective tasks such as open-domain question answering and mathematical reasoning, which can often be solved through recalling learned factual knowledg…
Dark Humor DetectionDialogue GenerationHumor DetectionMathematical Reasoning+2Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Models
Humor is a fundamental facet of human cognition and interaction. Yet, despite recent advances in natural language processing, humor detection remains a challenging task that is complicated by the scarcity of datasets tha…
Humor DetectionComment-aided Video-Language Alignment via Contrastive Pre-training for Short-form Video Humor Detection
The growing importance of multi-modal humor detection within affective computing correlates with the expanding influence of short-form video sharing on social media platforms. In this paper, we propose a novel two-branch…
FormHumor DetectionSOCIALITE-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. Instruction tuning has been s…
Humor DetectionReading ComprehensionFrom Generalized Laughter to Personalized Chuckles: Unleashing the Power of Data Fusion in Subjective Humor Detection
The vast area of subjectivity in Natural Language Processing (NLP) poses a challenge to the solutions typically used in generalized tasks. As exploration in the scope of generalized NLP is much more advanced, it implies …
Humor DetectionMMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts
Advances in multimodal models have greatly improved how interactions relevant to various tasks are modeled. Today's multimodal models mainly focus on the correspondence between images and text, using this for tasks like …
Binary ClassificationDescriptiveHumor DetectionImage-text matching+3