测试大模型跨领域推理能力，用一串组合题考出真实水平。
Relay-Bench: Evaluating LLMs on Multi-Domain Reasoning Chains
- 用多领域子问题串联成复合题，考模型跨域连贯推理
- 顶尖模型GPT-5.5(xHigh)仅达43.3%准确率
- 支持代码执行与网络搜索，适合评估真实工具使用能力
提出Relay-Bench，一个无饱和、全维度的纯文本基准，用于评估大模型在单个提示中完成多个不同领域任务的能力。测试集完全由复合问题构成：将单领域子问题串联成需跨领域联合推理的挑战。部分题目通过提示编码和刻意添加上下文冗余增加复杂度。涵盖视觉推理、编程、数学、信息提取（侧重网络搜索）、问题解决、通用知识和数据分析等领域。除模型调用限制外无其他约束，明确鼓励模型使用代码执行、网络搜索及所有可用工具。所有问题包含2至13个子问题，无需多模态输入输出。
原文摘要 · Abstract (English)
Introducing Relay-Bench, an unsaturated, holistic, text-only benchmark that measures LLMs' ability to complete an assortment of tasks from distinct domains in a single prompt. The leading model, GPT-5.5 (xHigh), scores 43.3%. The test set entirely consists of composite problems: groups of single-domain subproblems that are strung together into challenges that require reasoning across multiple domains in combination. Many of these problems then have layers of complexity added through prompt encoding and deliberate context bloat. Domains tested include visual reasoning, coding, math, information extraction (with a focus on web search), problem-solving, general knowledge, and data analysis. No restrictions are imposed outside of the model harness, and models are explicitly encouraged to leverage code-execution, web searches, and all available tools. All problems are composed of two to thirteen subproblems and do not require multi-modal input or output.
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