A new survey paper explores the challenges and methods for AI systems to understand and generate multimodal humor, particularly in visual formats like memes and comics. The research categorizes existing work by capabilities such as recognition, interpretation, and generation, highlighting the shift from specialized models to large multimodal models. The paper identifies key barriers to progress, including evaluation limitations, insufficient cultural knowledge, weak evidence grounding, and unresolved safety concerns. AI
IMPACT Highlights the limitations of current AI in understanding nuanced visual humor, suggesting a need for improved cultural knowledge and reasoning capabilities.
RANK_REASON The cluster consists of a survey paper published on arXiv and highlighted by Hugging Face, detailing methods and challenges in AI's understanding of multimodal humor.
Read on Hugging Face Daily Papers →
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- multimodal large language model
- Multimodal LLMs
- ScienceCast
- LLMs
- MLLMs
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