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Public Domain 12M: A Highly Aesthetic Image-Text Dataset with Novel Governance Mechanisms

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arxiv 2410.23144 v1 pith:EDNACU5Q submitted 2024-10-30 cs.AI

classification cs.AI
keywords datasetdomainpublicgovernanceimage-textmechanismsmodelsnovel
verification ladder T0 review T1 audit T2 compute T3 formal
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We present Public Domain 12M (PD12M), a dataset of 12.4 million high-quality public domain and CC0-licensed images with synthetic captions, designed for training text-to-image models. PD12M is the largest public domain image-text dataset to date, with sufficient size to train foundation models while minimizing copyright concerns. Through the Source.Plus platform, we also introduce novel, community-driven dataset governance mechanisms that reduce harm and support reproducibility over time.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model

    cs.CV 2026-06 unverdicted novelty 7.0 of 10

    AMALIA-VL introduces the first open-source instruction-tuned LVLM natively optimized for European Portuguese via vision-language alignment, instruction tuning, preference optimization, and a pt-PT-centric data mix.

  2. AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model

    cs.CV 2026-06 unverdicted novelty 6.0 of 10

    AMALIA-VL is the first open-source LVLM natively optimized for European Portuguese via three-stage training on a pt-PT-centric data mix combining curated, translated, and novel datasets.

  3. AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model

    cs.CV 2026-06 unverdicted novelty 6.0 of 10

    Introduces AMALIA-VL, the first open-source instruction-tuned LVLM for European Portuguese, using a high-resolution vision encoder, pt-PT language model, learned connector, and three-stage training on a custom data mix.

  4. Kwai Keye-VL 1.5 Technical Report

    cs.CV 2025-09 conditional novelty 6.0 of 10

    Keye-VL-1.5 combines similarity-based Slow-Fast video token allocation with progressive context extension and iterative RL, reporting leading video-understanding results among 8B-scale multimodal models.

  5. Kwai Keye-VL-2.0 Technical Report

    cs.CV 2026-06 unverdicted novelty 4.0 of 10

    Kwai Keye-VL-2.0-30B-A3B is a 30B MoE model with 3B active parameters using DSA adaptation and MOPD distillation that reports SOTA results on video understanding and agent benchmarks.

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