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# 【大模型北斗实习】统一化的检索生成框架探索与评测

北京市 +1 more 

Listed on Meituan ’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Meituan ’s careers site →](https://zhaopin.meituan.com/web/position/detail?highlightType=campus&jobUnionId=3153873006)

[OpenNash Jobs](https://jobs.opennash.com/) / [Meituan ](https://jobs.opennash.com/companies/meituan/) / 【大模型北斗实习】统一化的检索生成框架探索与评测

## Job description

引入外部知识检索是处理 agent 在有限记忆存储下知识局限性的主流路径（如检索增强生成），可以有效降低幻觉比例，使生成内容具备时效性和事实性。但现有问题是检索和生成模块通常作为异质系统交替使用，无法深度协同和统一优化。近期生成式检索方向的研究为二者统一创造了条件。

### 本课题希望彻底统一检索生成，研究内容包括但不限于

1）统一检索生成的推理和优化算法构建。 2）优化实验在数据和计算维度的规模化。 3）agent 视角对 RAG 和 long-context 的解读和相应评测评估方案。 4）从统一检索生成到模型记忆的外推。 1）熟悉大模型相关的推理、训练框架，有较强的工程实践能力和经验。 2）有一定的学术研究背景，对前沿技术保持好奇心，学习能力和自驱力强。

### 加分项

1）在有影响力的开源项目中做出核心贡献。 2）发表过高质量学术论文。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: Under a day
- Location: 北京市 +1 more[Apply on Meituan ’s careers site →](https://zhaopin.meituan.com/web/position/detail?highlightType=campus&jobUnionId=3153873006)

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