# AIArena: A Blockchain-Based Decentralized AI Training Platform

arXiv: https://arxiv.org/abs/2412.14566 · HTML: https://mlsanity.com/paper/2412.14566/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 13 references that are in the map.
- First posted on arXiv 19 Dec 2024.

## Builds on (most cited first, 5 of 5)

- [Proof-of-Learning: Definitions and Practice](https://mlsanity.com/paper/2103.05633/) (2021)
- [Model Watermarking for Image Processing Networks](https://mlsanity.com/paper/2002.11088/) (2020)
- [Defending Against Poisoning Attacks in Federated Learning with Blockchain](https://mlsanity.com/paper/2307.00543/) (2023)
- [SoK: Blockchain-Based Decentralized AI (DeAI)](https://mlsanity.com/paper/2411.17461/) (2024)
- [Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains](https://mlsanity.com/paper/2007.15145/) (2020)

## Built on by (most cited first, 4 of 4)

- [InfiCoEvalChain: A Blockchain-Based Decentralized Framework for Collaborative LLM Evaluation](https://mlsanity.com/paper/2602.08229/) (2026)
- [Counterweights and Complementarities: The Convergence of AI and Blockchain Powering a Decentralized Future](https://mlsanity.com/paper/2603.11299/) (2026)
- [Scaling Decentralized Learning with FLock](https://mlsanity.com/paper/2507.15349/) (2025)
- [SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence](https://mlsanity.com/paper/2605.10515/) (2026)

## Abstract (arXiv)

The rapid advancement of AI has underscored critical challenges in its development and implementation, largely due to centralized control by a few major corporations. This concentration of power intensifies biases within AI models, resulting from inadequate governance and oversight mechanisms. Additionally, it limits public involvement and heightens concerns about the integrity of model generation. Such monopolistic control over data and AI outputs threatens both innovation and fair data usage, as users inadvertently contribute data that primarily benefits these corporations. In this work, we propose AIArena, a blockchain-based decentralized AI training platform designed to democratize AI development and alignment through on-chain incentive mechanisms. AIArena fosters an open and collaborative environment where participants can contribute models and computing resources. Its on-chain consensus mechanism ensures fair rewards for participants based on their contributions. We instantiate and implement AIArena on the public Base blockchain Sepolia testnet, and the evaluation results demonstrate the feasibility of AIArena in real-world applications.