Reasoning about Intent for Ambiguous Requests

Researchers published a new approach to handling ambiguous requests in large language models on arXiv on November 25, 2025, version 2, aiming to reduce user frustration and safety risks caused by intent misunderstandings when AI systems commit to a single interpretation of unclear queries. The research addresses a significant challenge in artificial intelligence where large language models tend to respond to ambiguous prompts by implicitly selecting one interpretation, often leading to outcomes that don't match user expectations or potentially create safety concerns. To solve this problem, the researchers propose a novel method that generates multiple interpretation-answer pairs within a single structured response, allowing users to see and select the most appropriate interpretation of their request. This approach represents a significant advancement in how AI systems handle the inherent ambiguity of human language, potentially improving both user satisfaction and safety in AI applications.