TiM-Toy-T2I-Dataset / README.md
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metadata
task_categories:
  - text-to-image
license: apache-2.0
language:
  - en
tags:
  - diffusion-model
  - generative-ai
  - image-generation
  - toy-dataset

TiM-Toy-T2I-Dataset

This repository contains the toy dataset for text-to-image (T2I) generation used in the paper Transition Models: Rethinking the Generative Learning Objective.

Transition Models (TiM) introduce an exact, continuous-time dynamics equation that analytically defines state transitions across any finite time interval. This leads to a novel generative paradigm, TiM, which adapts to arbitrary-step transitions, seamlessly traversing the generative trajectory from single leaps to fine-grained refinement with more steps. This specific dataset serves as a toy dataset for training and experimentation with TiM for text-to-image generation.

Code: https://github.com/WZDTHU/TiM

Sample Usage

To download this toy text-to-image dataset for training TiM models, you can follow the instructions from the official GitHub repository under the "Dataset Setup" section:

bash tools/download_toy_t2i_dataset.sh

For more details on setting up the environment, downloading models, and other training/sampling scripts, please refer to the official GitHub repository.

Citation

If you find the project useful, please kindly cite:

@article{wang2025transition,
  title={Transition Models: Rethinking the Generative Learning Objective}, 
  author={Wang, Zidong and Zhang, Yiyuan and Yue, Xiaoyu and Yue, Xiangyu and Li, Yangguang and Ouyang, Wanli and Bai, Lei},
  year={2025},
  eprint={2509.04394},
  archivePrefix={arXiv},
  primaryClass={cs.LG}
}

License

This project is licensed under the Apache-2.0 license.