Question regarding the implementation of Hierarchical Clustering and U-Retrieval algorithm #26
Description
Hello, thank you very much for your work on Medical Graph RAG; the paper is excellent. I am reading the source code and trying to reproduce the experimental results in the paper, but I have found some inconsistencies when comparing the paper's description and the code implementation, and I would like to ask you about them.
1.Regarding hierarchical clustering: I noticed that the repository contains code for nano_graphrag (which implements Leiden clustering), but in the main logic of run.py (Standard Mode / else branch), it seems that these clustering algorithms are not called to build the semantic tree.
2.Regarding the retrieval logic (U-Retrieval): The core U-Retrieval in the paper is described as a top-down navigation retrieval based on a tree structure. However, in the seq_ret function of retrieve.py, I see that the logic is to retrieve all Summary nodes from the database, then loop through them and call LLM for scoring. This looks more like a full linear scan based on LLM, rather than the tree-based retrieval algorithm described in the paper.
I would like to ask: Is the currently open-source code a simplified demo? Are there plans to open-source the "12-layer dynamic clustering tree" construction and the actual U-Retrieval navigation code described in the paper? Or how can I reproduce the efficiency described in the paper based on the current code?
look forward to your reply, thank you!