---
id: 20260912-T0-10
title: "SearchAtlas：用证据查询图分析LLM搜索代理的策略过程"
title_en: "SearchAtlas Analyzes LLM Search Agent Strategies via Evidential Query Graphs"
url: https://ai.daily.yangsir.net/daily/20260912-T0-10
issue_date: 2026-09-12
publish_date: 2026-09-11T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2609.10901
---

# SearchAtlas：用证据查询图分析LLM搜索代理的策略过程

当前LLM搜索代理的评估多只看最终答案准确率，忽略了检索过程本身。SearchAtlas提出用证据查询图来分析搜索策略，通过追踪可信证据如何被检索以回答问题的约束条件，将原本埋在原始搜索日志里的过程信息结构化呈现。这项工作为理解和诊断搜索代理的行为提供了新工具，开发者可以用它定位代理在证据检索环节的薄弱点，而不只是看答对与否。

## English Version

**SearchAtlas Analyzes LLM Search Agent Strategies via Evidential Query Graphs**

LLM search agents are typically evaluated only on final-answer accuracy, overlooking the retrieval process itself. SearchAtlas introduces evidential query graphs to analyze search strategies by tracking how credible evidence is retrieved to address question constraints, structuring process information previously buried in raw search logs. This work provides a new tool for understanding and diagnosing search agent behavior. Developers can use it to pinpoint weaknesses in evidence retrieval, rather than judging only by whether the final answer is correct.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2609.10901)

**详情页**：https://ai.daily.yangsir.net/daily/20260912-T0-10

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