mlsanityData to 14 Oct 2026

DECORAIT -- DECentralized Opt-in/out Registry for AI Training

arXiv 2309.14400 ↗First posted 25 Sep 2023cs.CR cs.LG eess.IVcited by 7

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Abstract (arXiv)

We present DECORAIT; a decentralized registry through which content creators may assert their right to opt in or out of AI training as well as receive reward for their contributions. Generative AI (GenAI) enables images to be synthesized using AI models trained on vast amounts of data scraped from public sources. Model and content creators who may wish to share their work openly without sanctioning its use for training are thus presented with a data governance challenge. Further, establishing the provenance of GenAI training data is important to creatives to ensure fair recognition and reward for their such use. We report a prototype of DECORAIT, which explores hierarchical clustering and a combination of on/off-chain storage to create a scalable decentralized registry to trace the provenance of GenAI training data in order to determine training consent and reward creatives who contribute that data. DECORAIT combines distributed ledger technology (DLT) with visual fingerprinting, leveraging the emerging C2PA (Coalition for Content Provenance and Authenticity) standard to create a secure, open registry through which creatives may express consent and data ownership for GenAI.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 25 of its 42 references that are in the map. First posted on arXiv 25 Sep 2023.

Builds on

25 of 42 references.

References · 25

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  5. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  7. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
  8. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
  9. 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,877
  10. 2021LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairscited by 1,555
  11. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  12. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,106
13 more
  1. 2023Extracting Training Data from Diffusion Modelscited by 732
  2. 2022Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Modelscited by 424
  3. 2023InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuningcited by 345
  4. 2023Understanding and Mitigating Copying in Diffusion Modelscited by 209
  5. 2015Particular object retrieval with integral max-pooling of CNN activationscited by 161
  6. 2020Responsible Disclosure of Generative Models Using Scalable Fingerprintingcited by 91
  7. 2014IPFS - Content Addressed, Versioned, P2P File Systemcited by 70
  8. 2023RoSteALS: Robust Steganography using Autoencoder Latent Spacecited by 57
  9. 2019Decentralized & Collaborative AI on Blockchaincited by 21
  10. 2021OSCAR-Net: Object-centric Scene Graph Attention for Image Attributioncited by 15
  11. 2023EKILA: Synthetic Media Provenance and Attribution for Generative Artcited by 11
  12. 2018ARCHANGEL: Trusted Archives of Digital Public Documentscited by 7
  13. 2019ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchaincited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 3.

7 papers.

  1. 2025Content ARCs: Decentralized Content Rights in the Age of Generative AIcited by 3
  2. 2025A Framework for Cryptographic Verifiability of End-to-End AI Pipelinescited by 2
  3. 2024Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AIcited by 1
  4. 2024PDFed: Privacy-Preserving and Decentralized Asynchronous Federated Learning for Diffusion Modelscited by 1
  5. 2026Learning Probabilistic Embeddings for Unsupervised Action Segmentationcited by 1
  6. 2026Soft Redaction of Image Provenance via Zero-Knowledge Proofscited by 0
  7. 2026Signpost Watermarking: Joint Optimization for Visual Watermark Coexistencecited by 0