• Paper Title: ChainLM: Empowering the Future of Large Language Models through Blockchain-Powered Decentralization
  • Conference Name: JCCI
  • Abstract: The rapid growth of Large Language Models (LLMs) has revolutionized various fields, from natural language processing to AI-driven applications. However, the centralized nature of their development and deployment presents significant challenges in terms of accessibility, security, and control. This paper introduces ChainLM, a novel framework that leverages blockchain technology to decentralize access, thereby democratiz- ing their use. By utilizing blockchain’s inherent features of trans- parency, immutability, and decentralized consensus, ChainLM ensures that these models are not only accessible to a broader audience but also more secure, scalable, and fair. The frame- work enables open collaboration, incentivizes contributions from diverse stakeholders, and fosters trust by providing a transparent mechanism for model training and validation. Additionally, ChainLM addresses concerns regarding data privacy and model biases through decentralized data storage and federated learning techniques. This paper explores the technical architecture of ChainLM, its potential applications, and the broader implications of blockchain-powered decentralization in the AI landscape, paving the way for more equitable and trustworthy AI systems.
  • Status: Accepted
  • Conference Type: Domestic
  • Cite:
  • Author: Adnan
  • Write Date: 2025년 4월 28일 11:04 오전
  • Update Date: 2025년 4월 28일 11:04 오전
  • Visit Count: 1
  • Acknowledgment: None
  • File: No file attached