# Multi-Agent Fact Checking

arXiv: https://arxiv.org/abs/2503.02116 · HTML: https://mlsanity.com/paper/2503.02116/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Mar 2025.

## Built on by (most cited first, 3 of 3)

- [The Orchestration of Multi-Agent Systems: Architectures, Protocols, and Enterprise Adoption](https://mlsanity.com/paper/2601.13671/) (2026)
- [A Survey of Scaling in Large Language Model Reasoning](https://mlsanity.com/paper/2504.02181/) (2025)
- [TRUST Agents: A Collaborative Multi-Agent Framework for Fake News Detection, Explainable Verification, and Logic-Aware Claim Reasoning](https://mlsanity.com/paper/2604.12184/) (2026)

## Abstract (arXiv)

We formulate the problem of fake news detection using distributed fact-checkers (agents) with unknown reliability. The stream of news/statements is modeled as an independent and identically distributed binary source (to represent true and false statements). Upon observing a news, agent i labels the news as true or false which reflects the true validity of the statement with some probability 1-πi. In other words, agent i misclassified each statement with error probability πi∈ (0,1), where the parameter πi models the (un)trustworthiness of agent i. We present an algorithm to learn the unreliability parameters, resulting in a distributed fact-checking algorithm. Furthermore, we extensively analyze the discrete-time limit of our algorithm.