The field of multimodal research is moving towards a deeper understanding of how models process and generate cultural knowledge. Recent work has focused on evaluating the ability of diffusion models to recognize and reproduce cultural references, and how they transform and recontextualize this knowledge. Another area of interest is the detection of hallucinations in vision-language models, with a focus on developing frameworks that can accurately identify and mitigate these errors. Additionally, there is a growing interest in multimodal model editing, with a focus on developing evaluation methods that can accurately assess the success of edits. The application of multimodal models to specific domains, such as Indian poetry translation and image generation, is also an area of increasing research. Notable papers in this area include: The Persistence of Cultural Memory, which introduces an evaluation framework for assessing the ability of diffusion models to recognize and reproduce cultural references. HEDGE, which presents a unified framework for hallucination detection in vision-language models. Uncovering and Mitigating Transient Blindness, which proposes a comprehensive locality evaluation framework for multimodal model editing. Crossing Borders, which proposes a framework for Indian poetry translation and image generation.