# Solidago: A Modular Collaborative Scoring Pipeline

arXiv: https://arxiv.org/abs/2211.01179 · HTML: https://mlsanity.com/paper/2211.01179/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Oct 2022.

## Built on by (most cited first, 1 of 1)

- [A Case for Specialisation in Non-Human Entities](https://mlsanity.com/paper/2503.04742/) (2025)

## Abstract (arXiv)

This paper presents Solidago, an end-to-end modular pipeline to allow any community of users to collaboratively score any number of entities. Solidago proposes a six-module decomposition. First, it uses pretrust and peer-to-peer vouches to assign trust scores to users. Second, based on participation, trust scores are turned into voting rights per user per entity. Third, for each user, a preference model is learned from the user's evaluation data. Fourth, users' models are put on a similar scale. Fifth, these models are securely aggregated. Sixth, models are post-processed to yield human-readable global scores. We also propose default implementations of the six modules, including a novel trust propagation algorithm, and adaptations of state-of-the-art scaling and aggregation solutions. Our pipeline has been successfully deployed on the open-source platform tournesol.app. We thereby lay an appealing foundation for the collaborative, effective, scalable, fair, interpretable and secure scoring of any set of entities.