mlsanityData to 7 Oct 2026

Memotion Analysis through the Lens of Joint Embedding

arXiv 2111.07074 ↗First posted 13 Nov 2021cs.LG cs.AI cs.CLcited by 6

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Abstract (arXiv)

Joint embedding (JE) is a way to encode multi-modal data into a vector space where text remains as the grounding key and other modalities like image are to be anchored with such keys. Meme is typically an image with embedded text onto it. Although, memes are commonly used for fun, they could also be used to spread hate and fake information. That along with its growing ubiquity over several social platforms has caused automatic analysis of memes to become a widespread topic of research. In this paper, we report our initial experiments on Memotion Analysis problem through joint embeddings. Results are marginally yielding SOTA.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 13 Nov 2021.

Builds on

3 of 6 references.

References · 3

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2015Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Modelscited by 1,352
  3. 2020SemEval-2020 Task 8: Memotion Analysis -- The Visuo-Lingual Metaphor!cited by 77

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Citing papers per year: 2023: 5; 2024: 0; 2025: 1.

6 papers.