B ottle H umor: Self-Informed Humor Explanation using the Information Bottleneck Principle (2025)

Abstract: Humor is prevalent in online communications and it often relies on more than one modality (e.g., cartoons and memes).Interpreting humor in multimodal settings requires drawing on diverse types of knowledge, including metaphorical, sociocultural, and commonsense knowledge. However, identifying the most useful knowledge remains an open question. We introduce BottleHumor, a method inspired by the information bottleneck principle that elicits relevant world knowledge from vision and language models which is iteratively refined for generating an explanation of the humor in an unsupervised manner. Our experiments on three datasets confirm the advantage of our method over a range of baselines. Our method can further be adapted in the future for additional tasks that can benefit from eliciting and conditioning on relevant world knowledge and open new research avenues in this direction.

## introduction humor is an effective communication tool @xcite @xcite that can manifest in various forms, including puns, exaggerated facial expressions, absurd behaviors, and incongruities @xcite . it is shaped by multiple factors such as culture, social interactions, societal phenomena, and personal imagination @xcite . in particular, humor is prevalent in online communications @xcite , often spanning multiple modalities (e.g., cartoons and memes; @xcite . interpreting humor across modalities requires "reading between the lines", connecting textual and visual elements to grasp the meaning @xcite . for example, in fig. 1 , connecting the tooth fairy depicted in the image carrying a plunger to the caption, "in this economy, it's good to have an extra trade", creates the implications: a mundane plunger contrasts with the magical fairy. the caption humorously links it to economic struggles, suggesting even mythical beings need extra income. the child's sleep contrasts with the fairy's economic struggles, highlighting the absurdity of realworld hardship. ## bottlehumor given a humoristic image along with an accompanying text (caption), our goal is to generate a descriptive explanation of the humor. for example, in figure 2 , a fairy woman with a plunger looking at a boy can be humorously explained as "the humor comes from a fairy with a plunger, taking a side job because of a tough economy" (from the newyorker dataset; @xcite . we propose bottlehumor (figure 2 ), a multihop reasoning method inspired by the ib principle (sec. 3.1). we integrate the visual and textual components to generate implications (sec. 3.2). we then select the most useful implications by employing the ib principle ( sec. 3.3 ), and add them to the input to generate candidate explanations (sec. 3.4). this iterative process alternates between refining implications and explanations. ## results we present the comparison of bottlehumor to the baselines ( §5.1), look into the contribution of each individual component in our method ( §5.2), justify the ib framework ( §5.3), and present an error analysis of our method's predictions ( §5.3). ## conclusions we introduced bottlehumor, an unsupervised method inspired by the information bottleneck principle that addresses humor explanation tasks by eliciting relevant knowledge from vlms and iteratively refining the explanation. our experiments show that bottlehumor outperforms a range of baselines on three datasets, underscoring the importance of incorporating relevant world knowledge in humor understanding. our analysis offers insights into the impact of individual components in our method, and justifies the use of the ib principle. we further propose an llm-based evaluation framework and an adaptation of an interpretability technique. while we tested our contributions in the context of humor interpretation, future work can adapt them to any task that can benefit from eliciting and reasoning on world knowledge.