# RicciFlowRec: A Geometric Root Cause Recommender Using Ricci Curvature on Financial Graphs

arXiv: https://arxiv.org/abs/2508.09334 · HTML: https://mlsanity.com/paper/2508.09334/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 23 references that are in the map.
- First posted on arXiv 12 Aug 2025.

## Builds on (most cited first, 12 of 12)

- [Graph Attention Networks](https://mlsanity.com/paper/1710.10903/) (2017)
- [Explainable Recommendation: A Survey and New Perspectives](https://mlsanity.com/paper/1804.11192/) (2018)
- [Causal Embeddings for Recommendation](https://mlsanity.com/paper/1706.07639/) (2017)
- [Community Detection on Networks with Ricci Flow](https://mlsanity.com/paper/1907.03993/) (2019)
- [Ricci Curvature of the Internet Topology](https://mlsanity.com/paper/1501.04138/) (2015)
- [Breaking Down Financial News Impact: A Novel AI Approach with Geometric Hypergraphs](https://mlsanity.com/paper/2409.00438/) (2024)
- [Causal Spherical Hypergraph Networks for Modelling Social Uncertainty](https://mlsanity.com/paper/2506.17840/) (2025)
- [Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning](https://mlsanity.com/paper/2506.17826/) (2025)
- [Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling](https://mlsanity.com/paper/2404.07223/) (2024)
- [ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations](https://mlsanity.com/paper/2507.02014/) (2025)
- [Stress Testing Network Reconstruction via Graphical Causal Model](https://mlsanity.com/paper/1906.01468/) (2019)
- [Deep Causal Reasoning for Recommendations](https://mlsanity.com/paper/2201.02088/) (2022)

## Built on by (most cited first, 2 of 2)

- [From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere](https://mlsanity.com/paper/2510.04357/) (2025)
- [Knowledge or Calculator? Decomposing the Skill Premium in Verifiable Financial Agent Workflows](https://mlsanity.com/paper/2610.03564/) (2026)

## Abstract (arXiv)

We propose RicciFlowRec, a geometric recommendation framework that performs root cause attribution via Ricci curvature and flow on dynamic financial graphs. By modelling evolving interactions among stocks, macroeconomic indicators, and news, we quantify local stress using discrete Ricci curvature and trace shock propagation via Ricci flow. Curvature gradients reveal causal substructures, informing a structural risk-aware ranking function. Preliminary results on S&P~500 data with FinBERT-based sentiment show improved robustness and interpretability under synthetic perturbations. This ongoing work supports curvature-based attribution and early-stage risk-aware ranking, with plans for portfolio optimization and return forecasting. To our knowledge, RicciFlowRec is the first recommender to apply geometric flow-based reasoning in financial decision support.