---
格式版本: 2
标题: "Mitigating Context Interference for Reliable and Efficient Search Agents"
原文链接: "https://arxiv.org/abs/2608.10743"
发布日期: "2026-08-11"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "rule:local:strict_original_body"
发布时间证据: "**\\[v1\\]** Tue, 11 Aug 2026 10:00:42 UTC (1,175 KB)"
发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body"
发布时间校准置信度: "high"
发布时间候选数量: 18
发布时间严格候选数量: 6
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-12T11:29:50+08:00"
发布时间仲裁状态: "skipped"
发布时间仲裁尝试次数: 0
发布时间仲裁耗时毫秒: 0
发现时间: "2026-08-12T11:26:18+08:00"
入库时间: "2026-08-12T03:29:50.504Z"
来源平台: "arXiv 学术论文搜索"
搜索渠道: "source_template"
搜索词: "https://arxiv.org/search/?query=AI&searchtype=all"
匹配关键词:
  - "AI"
相关厂家:
  []
相关专家:
  []
内容类型: "网页"
抓取工具: "Free Fetch + Defuddle"
清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 10
AI分档: "非优质"
AI质检状态: "不通过"
AI打分理由: "论文主题为LLM搜索代理的上下文干扰，与超节点/AI Rack/机柜级AI基础设施完全无关，不涉及任何硬件架构、供电、散热、互连或量产落地。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-12T11:30:25+08:00"
AI主题相关性: 0
AI来源权威性: 0
AI新颖性: 0
AI技术细节: 0
AI商业部署信号: 0
AI完整性: 10
采集批次: "2026年8月12日2点04分20秒"
采集批次ID: "20260812-020420-289"
去重键: "https://arxiv.org/abs/2608.10743"
---

## Computer Science > Computation and Language

## Title:Mitigating Context Interference for Reliable and Efficient Search Agents

Authors:[Boyang Xue](https://arxiv.org/search/cs?searchtype=author&query=Xue,+B), [Bin Wu](https://arxiv.org/search/cs?searchtype=author&query=Wu,+B), [Shuofei Qiao](https://arxiv.org/search/cs?searchtype=author&query=Qiao,+S), [Sheng Wang](https://arxiv.org/search/cs?searchtype=author&query=Wang,+S), [Rui Wang](https://arxiv.org/search/cs?searchtype=author&query=Wang,+R), [Yiming Du](https://arxiv.org/search/cs?searchtype=author&query=Du,+Y), [Hongru Wang](https://arxiv.org/search/cs?searchtype=author&query=Wang,+H), [Jeff Z. Pan](https://arxiv.org/search/cs?searchtype=author&query=Pan,+J+Z), [Emine Yilmaz](https://arxiv.org/search/cs?searchtype=author&query=Yilmaz,+E), [Kam-Fai Wong](https://arxiv.org/search/cs?searchtype=author&query=Wong,+K), [Aldo Lipani](https://arxiv.org/search/cs?searchtype=author&query=Lipani,+A)

[View PDF](https://arxiv.org/pdf/2608.10743) [HTML (experimental)](https://arxiv.org/html/2608.10743v1)

> Abstract:Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts of multi-turn search agents are lengthy and complex. For example, the retrieved set of documents in each turn would inevitably introduce irrelevant information that distracts LLMs, referring to \\textit{context interference}, potentially hindering the reliability and efficiency of search agents. Therefore, we conduct a systematic study on context interference in multi-turn search agents, focusing on investigating i) which parts of the context of search agents will contribute to the context interference, ii) how to refine the contexts of search agents to mitigate the interference, and iii) can incorporating context refinement into search agent training yield further improvements. We reveal that interference primarily arises from the latest retrieved documents. Based on the explored findings, we then introduce a distill-based context refiner to dynamically mitigate context interference for multi-turn search agents. Finally, we validate that incorporating context refinement into RL training pipelines of search agents can significantly enhance both reliability and efficiency. This study highlights the importance of mitigating context interference of search agents, inspiring a novel paradigm of \`\`refine context and then generate'' for AI agents.

| Subjects: | Computation and Language (cs.CL) |
| --- | --- |
| Cite as: | [arXiv:2608.10743](https://arxiv.org/abs/2608.10743) \[cs.CL\] |
|  | (or [arXiv:2608.10743v1](https://arxiv.org/abs/2608.10743v1) \[cs.CL\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10743](https://doi.org/10.48550/arXiv.2608.10743) |

## Submission history

From: Boyang Xue \[[view email](https://arxiv.org/show-email/0fd95d3f/2608.10743)\]  
**\[v1\]** Tue, 11 Aug 2026 10:00:42 UTC (1,175 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10743) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
