MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched Contextualization
Published in ACL’23 (Main), 2023
Recommended citation: Shivam Sharma, Ramaneswaran S, Udit Arora, Md. Shad Akhtar, and Tanmoy Chakraborty. 2023. MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched Contextualization. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5272–5290, Toronto, Canada. Association for Computational Linguistics. https://aclanthology.org/2023.acl-long.289
The paper discusses the challenge of understanding the context of memes and introduces the MEMEX task. We create a dataset called MCC and propose a multimodal neural framework called MIME, which outperforms other models by 4% in F1-score. The study also provides detailed performance analyses and insights into cross-modal contextual associations.
Recommended citation: Shivam Sharma, Ramaneswaran S, Udit Arora, Md. Shad Akhtar, and Tanmoy Chakraborty. 2023. MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched Contextualization. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5272–5290, Toronto, Canada. Association for Computational Linguistics.