Sarcasm Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

9 leaderboard tables shown for this task, 9 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

14 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 76 papers with code (266 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
  1 Aug 2017 7 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  NLP tasks are often limited by scarcity of manually annotated data.
• A Large Self-Annotated Corpus for Sarcasm
  19 Apr 2017 6 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection.
• Scaling Language Models: Methods, Analysis & Insights from Training Gopher
  8 Dec 2021 3 repositories listed
  Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
• Sarcasm Detection using Hybrid Neural Network
  20 Aug 2019 3 repositories listed
  Sarcasm Detection has enjoyed great interest from the research community, however the task of predicting sarcasm in a text remains an elusive problem for machines.
• A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
  27 Oct 2016 3 repositories listed
  Sarcasm detection is a key task for many natural language processing tasks.
• Modelling Context with User Embeddings for Sarcasm Detection in Social Media
  4 Jul 2016 3 repositories listed
  We introduce a deep neural network for automated sarcasm detection.
• BloombergGPT: A Large Language Model for Finance
  30 Mar 2023 2 repositories listed
  The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering.
• UTNLP at SemEval-2022 Task 6: A Comparative Analysis of Sarcasm Detection Using Generative-based and Mutation-based Data Augmentation
  18 Apr 2022 2 repositories listed
  Using RoBERTa and mutation-based data augmentation, our best approach achieved an F1-sarcastic of 0.
• Training Compute-Optimal Large Language Models
  29 Mar 2022 2 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 4 pointer-only (licence)
  We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
• A Corpus of English-Hindi Code-Mixed Tweets for Sarcasm Detection
  30 May 2018 2 repositories listed
  Social media platforms like twitter and facebook have be- come two of the largest mediums used by people to express their views to- wards different topics.
• The Role of Conversation Context for Sarcasm Detection in Online Interactions
  19 Jul 2017 2 repositories listed
  To address the first issue, we investigate several types of Long Short-Term Memory (LSTM) networks that can model both the conversation context and the sarcastic response.
• Context-Dependent Sentiment Analysis in User-Generated Videos
  1 Jul 2017 2 repositories listed
  Multimodal sentiment analysis is a developing area of research, which involves the identification of sentiments in videos.
• Dual-level Adaptive Incongruity-enhanced Model for Multimodal Sarcasm Detection
  7 Jan 2025 1 repository listed
  Existing methods primarily focused on the incongruity between text and image information for sarcasm detection.
• RCLMuFN: Relational Context Learning and Multiplex Fusion Network for Multimodal Sarcasm Detection
  17 Dec 2024 1 repository listed
  Finally, we employ a multiplex feature fusion module to enhance the generalization of the model by penetratingly integrating multimodal features derived from various interaction contexts.
• Gender Bias Mitigation for Bangla Classification Tasks
  16 Nov 2024 1 repository listed
  In this study, we investigate gender bias in Bangla pretrained language models, a largely under explored area in low-resource languages.
• An Innovative CGL-MHA Model for Sarcasm Sentiment Recognition Using the MindSpore Framework
  2 Nov 2024 1 repository listed
  The pervasive use of the Internet and social media introduces significant challenges to automated sentiment analysis, particularly for sarcastic expressions in user-generated content.
• Sarcasm Detection in a Less-Resourced Language
  16 Oct 2024 1 repository listed
  The sarcasm detection task in natural language processing tries to classify whether an utterance is sarcastic or not.
• InterCLIP-MEP: Interactive CLIP and Memory-Enhanced Predictor for Multi-modal Sarcasm Detection
  24 Jun 2024 1 repository listed
  Sarcasm in social media, often expressed through text-image combinations, poses challenges for sentiment analysis and intention mining.
• CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models
  1 May 2024 1 repository listed Syntology ran 17 of 21 samples · 4 unverified · 21 pointer-only (licence)
  Current methods for Multimodal Sarcasm Target Identification (MSTI) predominantly focus on superficial indicators in an end-to-end manner, overlooking the nuanced understanding of multimodal sarcasm conveyed through…
• Generalizable Sarcasm Detection Is Just Around The Corner, Of Course!
  9 Apr 2024 1 repository listed
  We tested the robustness of sarcasm detection models by examining their behavior when fine-tuned on four sarcasm datasets containing varying characteristics of sarcasm: label source (authors vs.
• Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment
  11 Mar 2024 1 repository listed
  Multi-modal semantic understanding requires integrating information from different modalities to extract users' real intention behind words.
• KoCoSa: Korean Context-aware Sarcasm Detection Dataset
  22 Feb 2024 1 repository listed
  In this paper, we introduce a new dataset for the Korean dialogue sarcasm detection task, KoCoSa (Korean Context-aware Sarcasm Detection Dataset), which consists of 12.
• DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding
  26 Dec 2023 1 repository listed
  Multimodal Sarcasm Understanding (MSU) has a wide range of applications in the news field such as public opinion analysis and forgery detection.
• MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts
  16 Nov 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Advances in multimodal models have greatly improved how interactions relevant to various tasks are modeled.
• Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary Tasks
  14 Sep 2023 1 repository listed
  However, prior work on multimodal classification of social media posts has not yet addressed these challenges.
• A Wide Evaluation of ChatGPT on Affective Computing Tasks
  26 Aug 2023 1 repository listed
  In this work, we widely study the capabilities of the ChatGPT models, namely GPT-4 and GPT-3.
• MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection System
  14 Jul 2023 1 repository listed
  Multi-modal sarcasm detection has attracted much recent attention.
• A big data approach towards sarcasm detection in Russian
  1 Jun 2023 1 repository listed
  We present a set of deterministic algorithms for Russian inflection and automated text synthesis.
• Borrowing Human Senses: Comment-Aware Self-Training for Social Media Multimodal Classification
  27 Mar 2023 1 repository listed
  Social media is daily creating massive multimedia content with paired image and text, presenting the pressing need to automate the vision and language understanding for various multimodal classification tasks.
• TEDB System Description to a Shared Task on Euphemism Detection 2022
  16 Jan 2023 1 repository listed
  In this report, we describe our Transformers for euphemism detection baseline (TEDB) submissions to a shared task on euphemism detection 2022.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.