Hateful Meme Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 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

5 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.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

9 shown of 9 papers with code (17 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.

• Learning Transferable Visual Models From Natural Language Supervision
  26 Feb 2021 82 repositories listed Syntology ran 16 of 20 samples · 4 unverified · 16 pointer-only (licence)
  State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories.
• Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection
  18 Feb 2025 1 repository listed Syntology ran 2 of 4 samples · 2 unverified
  Hateful memes have become a significant concern on the Internet, necessitating robust automated detection systems.
• Prompt-enhanced Network for Hateful Meme Classification
  12 Nov 2024 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  Specifically, after constructing the sequence through the prompt method and encoding it with a language model, we performed region information global extraction on the encoded sequence for multi-view perception.
• MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification
  23 Sep 2024 1 repository listed
  We further compare the performance of MemeCLIP and zero-shot GPT-4 on the hate classification task.
• Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
  24 Jan 2024 1 repository listed Syntology ran 4 of 6 samples · 2 unverified
  Then we propose to fine-tune a small language model as the debate judge for harmfulness inference, to facilitate multimodal fusion between the harmfulness rationales and the intrinsic multimodal information within memes.
• Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning
  14 Nov 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Hateful memes have emerged as a significant concern on the Internet.
• Mapping Memes to Words for Multimodal Hateful Meme Classification
  12 Oct 2023 1 repository listed Syntology ran 2 of 3 samples · 1 unverified
  Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions.
• Decoding the Underlying Meaning of Multimodal Hateful Memes
  28 May 2023 1 repository listed
  Recent studies have proposed models that yielded promising performance for the hateful meme classification task.
• Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features
  12 Oct 2022 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  A simple classifier based on the FIM representation is able to achieve state-of-the-art performance on the Hateful Memes Challenge (HMC) dataset with an AUROC of 85.

Syntology lines on 7 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.