DeepSeek团队提出千图假说，解决大型代码库推理问题，无需预构建关系图就能达到95.6%成功率。
DeepSeek-V4-Flash模型在SWE-bench Verified基准测试中，通过两层索引分离全局路由与局部实体焦点，实现了零预构建实体关系边条件下的95.6%成功率。研究提出了一种仅实体的外部接口，在推理过程中实现任务条件关系物化。基础、单层和双层条件分别达到92.1%、94.2%和95.6%的成功率。
The Thousand-Graph Hypothesis: A Testable Hypothesis of Task-Conditioned Relation Materialization in Repository-Level Code Reasoning
Large software repositories are often beyond model context limits. Training repository knowledge into models is costly and quickly stale, while local retrieval can miss scattered requirements, and explicit relation graphs add ongoing maintenance burden. We propose an entity-only external interface with task-conditioned relation materialization during inference. A two-layer index separates global routing from local entity focus and is evaluated on DeepSeek-V4-Flash and SWE-bench Verified. The base, one-layer, and two-layer conditions achieve 92.1%, 94.2%, and 95.6% success, respectively, under zero pre-built entity-relation edges.