Ai2's XYBench tests whether AI assistants catch misguided questions

Nov 13, 2026
In 8,115 questions, leading models helped with the mistaken approach instead of steering users to their real goal.

The Allen Institute for AI has released XYBench, a benchmark of 8,115 questions that tests whether AI assistants notice when a user asks about the wrong approach to a problem, Ai2 announced. It is named after the "XY problem," where someone wants X, assumes Y will get them there and asks only about Y.

Built with researchers at Carnegie Mellon, Nvidia and Johns Hopkins from Stack Overflow, Stack Exchange and WikiHow material, the benchmark covers programming, cooking and home repair. Models tested, including Claude Sonnet 4.6, GPT-5, Gemini 3.1 Pro and DeepSeek-V4 Pro, often kept their answers focused on the mistaken approach, unlike human reference answers. The paper won Best Resource Paper at EMNLP 2026.

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