Researchers studied how a language model responds to indirect prompts in three languages: English, Tamil, and a mix of both. They found that when the model is given reasoning information, it's more likely to ignore malicious instructions. However, the study's small size means its findings may not be generalizable. The researchers provide a reproducible case study of how visible reasoning can inform behavior in language models. --- Why it matters: Understanding how language models respond to indirect prompts is crucial for developing safe and trustworthy AI systems. This research provides insights into how visible reasoning can improve model behavior, but more studies are needed to confirm its effectiveness and generalizability. Source: https://arxiv.org/abs/2608.15392