AGE: Adaptive-masking for Graph Embedding in Graph Retrieval-Augmented Generation
- 类型:arxiv
- 标识:2607.00052
- 链接:https://arxiv.org/abs/2607.00052
- 主分类:rag
- 形态:method
- 被引:0
- 被引来源:Semantic Scholar + OpenAlex
- S2被引:0
- OpenAlex被引:0
- 影响力被引:0
- TLDR:AGE focuses on predicting nodes apart from key nodes, utilizing a learnable node sampler, and significantly improves approaches using non-parametric search component in GraphQA tasks, achieving superior accuracy across four benchmark datasets with distinct characteristics.
- OpenAlex ID:W7167091014
- OpenAlex DOI:10.48550/arxiv.2607.00052
- DOI:10.48550/arxiv.2607.00052
- DOI来源:OpenAlex
- 开放获取:green
- 开放获取链接:https://doi.org/10.48550/arxiv.2607.00052
- OpenAlex更新:2026-07-19
- 待LLM分类:否
- 标题中文:AGE:面向图检索增强生成中图嵌入的自适应掩码方法
- TLDR中文:AGE 专注于预测关键节点以外的节点,采用可学习节点采样器,在基于非参数检索组件的 GraphQA 任务上取得显著提升,在四个具有不同特征的基准数据集上均达到更高的准确率。
- 来源文件:
- /inbox/tom/_candidates/2026-07-06-agent-rag-longcontext-candidates.json
- [S2 enrich]
- [OpenAlex backfill]