BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models
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Abstract (arXiv)
In recent years, artificial intelligence (AI) and machine learning (ML) are reshaping society's production methods and productivity, and also changing the paradigm of scientific research. Among them, the AI language model represented by ChatGPT has made great progress. Such large language models (LLMs) serve people in the form of AI-generated content (AIGC) and are widely used in consulting, healthcare, and education. However, it is difficult to guarantee the authenticity and reliability of AIGC learning data. In addition, there are also hidden dangers of privacy disclosure in distributed AI training. Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition. The above information security issues in the coming era of AI powered by LLMs will be infinitely amplified and affect everyone's life. Therefore, we consider empowering LLMs using blockchain technology with superior security features to propose a vision for trusted AI. This paper mainly introduces the motivation and technical route of blockchain for LLM (BC4LLM), including reliable learning corpus, secure training process, and identifiable generated content. Meanwhile, this paper also reviews the potential applications and future challenges, especially in the frontier communication networks field, including network resource allocation, dynamic spectrum sharing, and semantic communication. Based on the above work combined and the prospect of blockchain and LLMs, it is expected to help the early realization of trusted AI and provide guidance for the academic community.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 62 of its 175 references that are in the map. First posted on arXiv 10 Oct 2023.
Builds on
62 of 175 references.
References · 62
- 2017Attention Is All You Needcited by 60,361
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
- 2014Explaining and Harnessing Adversarial Examplescited by 7,364
- 2023A Survey of Large Language Modelscited by 2,576
- 2022Emergent Abilities of Large Language Modelscited by 2,512
- 2020Extracting Training Data from Large Language Modelscited by 2,189
- 2023A Survey on Evaluation of Large Language Modelscited by 1,242
- 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
38 more
- 2023BloombergGPT: A Large Language Model for Financecited by 939
- 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 938
- 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
- 2021Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LMcited by 632
- 2021FinQA: A Dataset of Numerical Reasoning over Financial Datacited by 562
- 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
- 2022Reducing Activation Recomputation in Large Transformer Modelscited by 302
- 2023FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learningcited by 149
- 2021Semantic Communications: Principles and Challengescited by 91
- 2022On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Modelcited by 81
- 2020Impact of News on the Commodity Market: Dataset and Resultscited by 80
- 2022Recovering Private Text in Federated Learning of Language Modelscited by 70
- 2023AI-Generated Content (AIGC): A Surveycited by 59
- 2022Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Modelscited by 53
- 2023ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT modelscited by 42
- 2023A Pathway Towards Responsible AI Generated Contentcited by 38
- 2023A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutionscited by 35
- 2023Large AI Model-Based Semantic Communicationscited by 35
- 2023Integration of Large Language Models and Federated Learningcited by 31
- 2023Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networkscited by 26
- 2021Non-Fungible Token (NFT): Overview, Evaluation, Opportunities and Challengescited by 25
- 2023AI-Generated Image Detection using a Cross-Attention Enhanced Dual-Stream Networkcited by 22
- 2023Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networkscited by 21
- 2019PIRATE: A Blockchain-based Secure Framework of Distributed Machine Learning in 5G Networkscited by 18
- 2022Prompt-Augmented Linear Probing: Scaling beyond the Limit of Few-shot In-Context Learnerscited by 18
- 2023Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbotscited by 18
- 2022Fusing Blockchain and AI with Metaverse: A Surveycited by 17
- 2023Blockchain Large Language Modelscited by 17
- 2022Trustworthy Federated Learning via Blockchaincited by 15
- 2023Blockchain-aided Secure Semantic Communication for AI-Generated Content in Metaversecited by 15
- 2023Semantic Importance-Aware Communications Using Pre-trained Language Modelscited by 15
- 2019Efficient Adaptation of Pretrained Transformers for Abstractive Summarizationcited by 13
- 2023Semantic Communication with Memorycited by 13
- 2022Top-N Recommendation Algorithms: A Quest for the State-of-the-Artcited by 12
- 2023ChatGPT: Vision and Challengescited by 11
- 2021Blockchain Systems, Technologies and Applications: A Methodology Perspectivecited by 6
- 2018A Survey on Essential Components of a Self-Sovereign Identitycited by 4
- 2018Security Services Using Blockchains: A State of the Art Surveycited by 3
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Citing papers per year: 2024: 4; 2025: 1; 2026: 1.
6 papers.
- 2024Blockchain for Large Language Model Security and Safety: A Holistic Surveycited by 8
- 2024Federated TrustChain: Blockchain-Enhanced LLM Training and Unlearningcited by 3
- 2024Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Healthcited by 2
- 2025From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communicationscited by 2
- 2024Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaborationcited by 1
- 2026From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architecturescited by 0
- 2026From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures1 Oct 2026
- 2025From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications28 May 2025
- 2024Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration18 Dec 2024
- 2024Blockchain for Large Language Model Security and Safety: A Holistic Survey26 Jul 2024
- 2024Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health19 Jun 2024
- 2024Federated TrustChain: Blockchain-Enhanced LLM Training and Unlearning6 Jun 2024