MemeIntent: Benchmarking Intent Description Generation for Memes

Jeongsik Park, Khoi P. N. Nguyen, Terrence Li, Suyesh Shrestha, Megan Kim Vu, Jerry Yining Wang, and Vincent Ng
Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp. 631-643, 2024.

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Abstract

While recent years have seen a surge of interest in the automatic processing of memes, much of the work in this area has focused on determining whether a meme contains malicious content. This paper proposes the new task of intent description generation: generating a description of the author’s intentions when creating the meme. To stimulate future work on this task, we (1) annotated a corpus of memes with the intents being perceived by the reader as well as the background knowledge needed to infer the intents and (2) established baseline performance on the intent description generation task using state-of-the-art large language models. Our results suggest the importance of background knowledge retrieval in intent description generation for memes.

Dataset

The dataset used in this paper is available from this page.

BibTeX entry

@InProceedings{Park+etal:24a,
  author = {Jeongsik Park and Khoi Nguyen and Terrence Li and Suyesh Shrestha and Megan Vu and Jerry Wang and Vincent Ng},
  title = {MemeIntent: Benchmarking Intent Description Generation for Memes},
  booktitle = {Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue},
  pages = {631--643}, 
  year = 2024}