Researchers investigated whether large language models (LLMs) can learn to understand figurative language by fine-tuning them on cultural data. They tested four LLMs on six Arabic datasets and found that fine-tuning on poetry improved idiom comprehension, but cultural fine-tuning had mixed results. The study suggests that the relationship between culture and figurative language is complex and not easily captured through fine-tuning alone. --- Why it matters: This research matters to AI engineers because it highlights the challenges of transferring knowledge across different domains, particularly when it comes to culturally embedded concepts like figurative language. Understanding how LLMs can be fine-tuned to improve their performance on these tasks is crucial for developing more effective and nuanced language models. Source: https://arxiv.org/abs/2608.18361