I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition
arXiv:2606.05316v1 Announce Type: new Abstract: Multimodal memes are dynamic and often require up to date background knowledge for interpretation. Existing methods often overlook such knowledge or rely on fixed parametric knowledge of pretrained models that may be incomplete, outdated, or unavailable for emerging memes. We introduce Query Retrieve Conclude, a zero shot framework that identifies missing knowledge, retrieves open web evidence, and synthesizes evidence grounded background knowledge for meme understanding and detection. We also introduce a curated meme understanding benchmark of r
The rapid evolution and proliferation of multimodal content, particularly memes, necessitate more adaptive AI understanding capabilities to keep pace with dynamic cultural shifts.
This research directly addresses the challenge of AI lagging behind rapidly emerging societal information, impacting AI's ability to interpret nuanced and evolving human communication.
AI models will become more adept at understanding novel and contextual information without constant retraining, improving their relevance and utility in dynamic environments.
- · AI developers
- · Open-source data platforms
- · Social media analytics
- · Content moderation platforms
- · Static AI models
- · Closed-source knowledge bases
AI systems will gain a significantly improved ability to parse and react to emergent cultural phenomena and rapidly evolving community-specific language.
Enhanced meme understanding could lead to more nuanced sentiment analysis and trend prediction for online communities, influencing marketing and public opinion monitoring.
The methodology could generalize to other forms of dynamic, contextual information, accelerating the development of more human-like, adaptive AI agents.
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Read at arXiv cs.AI