让AI理解新梗，靠实时搜索补充背景知识。
I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition
- 零样本框架动态检索网络信息补全理解短板。
- 在3个理解数据集和5个检测任务中表现优于基线。
- 专为2024至2026年新梗设计，适合研究新兴文化现象。
多模态表情包动态变化，常需最新背景知识才能理解。现有方法往往忽略此类知识，或依赖预训练模型中固定、过时或缺失的参数化知识，难以应对新出现的梗。我们提出Query Retrieve Conclude框架，实现零样本下识别缺失知识、从开放网络检索证据，并合成基于证据的背景知识以支持表情包理解与检测。同时构建了一个涵盖2024至2026年新梗的精选表情包理解基准，附带外部背景知识标注。在三个表情包理解数据集和五个表情包检测任务上的实验表明，该框架在知识恢复、理解能力及下游检测性能上均优于零样本基线。
原文摘要 · Abstract (English)
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often overlook such knowledge or rely on fixed parametric knowledge of pretrained models that may be incomplete, outdated, or unavailable for emerging memes.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 recent memes from 2024 to 2026 with external background knowledge annotations. Experiments on three meme understanding datasets and five meme detection tasks show that our framework improves knowledge recovery, meme understanding and downstream detection over zero shot baselines.
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