# Energy-Based Diffusion Language Models for Text Generation

Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat. ICLR 2025 (2025).

Adds a full-sequence residual energy to each diffusion denoising distribution, with autoregressive or NCE parameterizations and parallel importance sampling.

Directly cites Deng et al. (2020), carrying residual correction and partition estimation into diffusion language modeling.

[Original paper](https://arxiv.org/html/2410.21357v4)

## Citation

```bibtex
@inproceedings{edlm,
  title = {{Energy-Based Diffusion Language Models for Text Generation}},
  author = {Xu, Minkai and Geffner, Tomas and Kreis, Karsten and Nie, Weili and Xu, Yilun and Leskovec, Jure and Ermon, Stefano and Vahdat, Arash},
  year = {2025},
  booktitle = {ICLR 2025},
  url = {https://arxiv.org/html/2410.21357v4},
  eprint = {2410.21357},
  archivePrefix = {arXiv}
}
```