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Dall-eval: Probing the reasoning skills and social biases of text-to-image generative transformers

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

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citation-polarity summary

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cs.CV 2 cs.AI 1

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2026 1 2022 2

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representative citing papers

Video Diffusion Models

cs.CV · 2022-04-07 · unverdicted · novelty 7.0

A diffusion model for video generation extends image architectures with joint image-video training and improved conditional sampling, delivering first large-scale text-to-video results and state-of-the-art performance on video prediction and unconditional generation benchmarks.

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Showing 3 of 3 citing papers.

  • Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding cs.CV · 2022-05-23 · accept · none · ref 10

    Imagen achieves state-of-the-art photorealistic text-to-image generation by scaling a text-only pretrained T5 language model within a diffusion framework, reaching FID 7.27 on COCO without training on it.

  • Video Diffusion Models cs.CV · 2022-04-07 · unverdicted · none · ref 12

    A diffusion model for video generation extends image architectures with joint image-video training and improved conditional sampling, delivering first large-scale text-to-video results and state-of-the-art performance on video prediction and unconditional generation benchmarks.

  • Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models cs.AI · 2026-04-22 · unverdicted · none · ref 8

    Target-based prompting lets users define fairness distributions for skin tones in generative AI, shifting outputs closer to chosen targets across 36 tested prompts for occupations and contexts.