这篇论文提醒我们，别以为结构化输出只是换个格式，它可能悄悄让模型回答变得更单调。做Agent开发的朋友应该看看。
康奈尔大学一项新研究测试了44个模型，发现要求JSON格式输出会使答案同质化，模态答案比例从41%升至64%，不同答案数量从52降至36。JSON和XML有这种效应，YAML和CSV没有。解码器强制schema不会进一步压缩，说明问题出在模型对格式的响应模式。该发现对依赖JSON模式的智能体管道有重要影响。
Are structured outputs in agents always good? This paper suggests that you might have to take a clo...
Are structured outputs in agents always good? This paper suggests that you might have to take a closer look. Your product's structured output surface is measurably more homogeneous than the chat surface you benchmarked it on. Teams treat structured output as a formatting choice with no effect on content. This new work from Cornell tests that assumption across 44 models and finds the format itself reshapes the answers. On an open-ended pick-a-word prompt, simply requesting JSON pushes the modal answer from 41% to 64% of responses and cuts distinct answers from 52 to 36. The collapse shows up for JSON and XML, the formats models were post-trained to emit, and disappears for YAML and CSV. Enforcing a schema at the decoder compresses nothing further, which points the narrowing back to how the model answers the register itself. Why does it matter? Any pipeline leaning on JSON mode for variety is sampling from a smaller pool than it thinks. Paper. arxiv.org/abs/2607.18476 Learn to build effective AI agents in our academy. academy.dair.ai 💬 5 🔄 3 ❤️ 12 👀 1711 📊 8 ⚡