TY  - JOUR
TI  - LAION-5B (open image-text training dataset)
AU  - Schuhmann, C.
AU  - Beaumont, R.
AU  - Vencu, R.
AU  - Gordon, C.
AU  - Wightman, R.
AU  - Cherti, M.
AU  - Coombes, T.
AU  - Katta, A.
AU  - Mullis, C.
AU  - Wortsman, M.
AU  - et al.
PY  - 2022
DA  - 2022/10//
JO  - NeurIPS 2022 Datasets and Benchmarks
AB  - Schuhmann et al. (2022) released LAION-5B, an open dataset of approximately 5.85 billion image-text pairs assembled by filtering Common Crawl web data using CLIP similarity scores. Stable Diffusion and the majority of open generative image models were trained on LAION-5B subsets, making it the concrete training-data substrate beneath the open generative-AI ecosystem. The dataset is named in the Andersen v Stability AI copyright litigation as the dataset at issue, creating a direct link between the technical and legal entries in the repository. Teaching data provenance, consent, scraping ethics and copyright exposure in AI image generation requires understanding LAION-5B specifically.
KW  - training-data
KW  - ip-and-copyright
KW  - generative-ai
UR  - https://arxiv.org/abs/2210.08402
LA  - en
ER  -