XYBench: Helping with the problem behind the question
Source
huggingface.co
Date
Why it matters
Assistants often answer the literal question and miss the real problem behind it. XYBench gives you 8K+ real questions to measure whether your assistant or AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → redirects users toward their actual goal.
Key takeaways · AI-distilled
Ai2 found that all five models tested (including Claude Sonnet 4.6, GPT-5 and Gemini 3.1 Pro) offered fixes for the literal request more often than for the real goal. On Stack Overflow, 75-86% of answers solved the stated request versus 59-71% for the underlying goal.
Mentioning the right fix is not the same as leading with it. The authors scored emphasis separately: on Stack Overflow, models focused mainly on the underlying goal in only 35-41% of answers and on the mistaken approach in 47-57%.
Models can recognize good advice better than they write it. Shown a literal answer and a goal-focused one, six models picked the goal-focused answer 71-84% of the time on Stack Overflow, which the authors say a multiple-choice test alone would not reveal.
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
