mlsanityData to 7 Oct 2026

An Interpretable Approach to Hateful Meme Detection

arXiv 2108.10069 ↗First posted 9 Aug 2021cs.LG cs.CLcited by 3

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Abstract (arXiv)

Hateful memes are an emerging method of spreading hate on the internet, relying on both images and text to convey a hateful message. We take an interpretable approach to hateful meme detection, using machine learning and simple heuristics to identify the features most important to classifying a meme as hateful. In the process, we build a gradient-boosted decision tree and an LSTM-based model that achieve comparable performance (73.8 validation and 72.7 test auROC) to the gold standard of humans and state-of-the-art transformer models on this challenging task.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 17 of its 29 references that are in the map. First posted on arXiv 9 Aug 2021.

Builds on

17 of 29 references.

References · 17

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  2. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
  3. 2015A large annotated corpus for learning natural language inferencecited by 1,837
  4. 2015Show, Attend and Tell: Neural Image Caption Generation with Visual Attentioncited by 1,421
  5. 2019Adversarial NLI: A New Benchmark for Natural Language Understandingcited by 798
  6. 2020The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memescited by 485
  7. 2018Combining Fact Extraction and Verification with Neural Semantic Matching Networkscited by 120
  8. 2020SemEval-2020 Task 8: Memotion Analysis -- The Visuo-Lingual Metaphor!cited by 77
  9. 2020Detecting Hate Speech in Memes Using Multimodal Deep Learning Approaches: Prize-winning solution to Hateful Memes Challengecited by 51
  10. 2020Vilio: State-of-the-art Visio-Linguistic Models applied to Hateful Memescited by 50
  11. 2020A Multimodal Framework for the Detection of Hateful Memescited by 48
  12. 2018On the Origins of Memes by Means of Fringe Web Communitiescited by 45
5 more
  1. 2020Enhance Multimodal Transformer With External Label And In-Domain Pretrain: Hateful Meme Challenge Winning Solutioncited by 41
  2. 2020Detecting Hateful Memes Using a Multimodal Deep Ensemblecited by 30
  3. 2021DeepHate: Hate Speech Detection via Multi-Faceted Text Representationscited by 29
  4. 2020A Multimodal Memes Classification: A Survey and Open Research Issuescited by 14
  5. 2018Named Entity Recognition on Noisy Data using Images and Text (1-page abstract)cited by 1

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Cited by year

Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2024Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicitiescited by 13
  2. 2024Exploring the Limits of Zero Shot Vision Language Models for Hate Meme Detection: The Vulnerabilities and their Interpretationscited by 10
  3. 2023Causal Intersectionality and Dual Form of Gradient Descent for Multimodal Analysis: a Case Study on Hateful Memescited by 2