The Riddle of Reflection: Evaluating Reasoning and Self-Awareness in Multilingual LLMs using Indian Riddles

A recent study investigates the ability of large language models (LLMs) to understand and reason with traditional Indian riddles across seven major languages. By developing a unique dataset that combines classic riddles with contextually adapted versions, the research evaluates the reasoning and self-awareness of five different LLMs. The focus is on assessing how these models perform in culturally rich contexts, highlighting their capacity for nuanced understanding beyond straightforward language tasks. This evaluation sheds light on the models' reasoning capabilities, particularly in handling culturally embedded content. The study contributes to ongoing efforts to benchmark LLMs in diverse linguistic and cultural settings, providing insights into their strengths and limitations. Such work is crucial for advancing AI systems that can engage meaningfully with varied cultural knowledge.