DIFFA Series

🔥 News

• 2026.04.07: DIFFA-2 is accepted by Findings of ACL 2026 !
• 2026.03.03: Released the DIFFA-2 checkpoint and code.
• 2026.01: Our new paper DIFFA-2 is now available on arXiv. 🎉
• 2025.11: DIFFA has been accepted to AAAI 2026!
• 2025.08: Released the DIFFA checkpoint and code.
• 2025.07: Our paper DIFFA is available on arXiv. 🎉

[Findings of ACL 2026] DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding

In this paper, We introduce DIFFA-2, a practical diffusion-based LALM for general audio understanding. DIFFA-2 upgrades the speech encoder, employs dual semantic and acoustic adapters, and is trained with a four-stage curriculum that combines semantic and acoustic alignment, large-scale supervised fine-tuning, and variance-reduced preference optimization, using only fully open-source corpora. Experiments on MMSU, MMAU, and MMAR show that DIFFA-2 consistently improves over DIFFA and is competitive to strong AR LALMs under practical training budgets, supporting diffusion-based modeling is a viable backbone for large-scale audio understanding.

[AAAI 2026] DIFFA: Large Language Diffusion Models Can Listen and Understand

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DIFFA is the first diffusion-based large audio-language model (LALM) for spoken language understanding.
It leverages a frozen diffusion LLM with dual adapters (semantic + acoustic) to enhance audio perception and reasoning.
As the first exploration of diffusion-based large language models (dLLMs) in speech and audio understanding, DIFFA opens new directions for non-autoregressive multimodal learning. This repository provides the training data, checkpoints, inference scripts, and reproducible training pipelines to facilitate further research on diffusion LLMs in the audio domain.

📖 Citation

If you find DIFFA useful, please cite:

@article{zhou2026diffa,
  title={DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding},
  author={Zhou, Jiaming and Cheng, Xuxin and Zhao, Shiwan and Jia, Yuhang and Liu, Cao and Zeng, Ke and Cai, Xunliang and Qin, Yong},
  journal={arXiv preprint arXiv:2601.23161},
  year={2026}
}

@article{zhou2025diffa,
  title={DIFFA: Large Language Diffusion Models Can Listen and Understand},
  author={Zhou, Jiaming and Chen, Hongjie and Zhao, Shiwan and Kang, Jian and Li, Jie and Wang, Enzhi and Guo, Yujie and Sun, Haoqin and Wang, Hui and Kong, Aobo and others},
  journal={arXiv preprint arXiv:2507.18452},
  year={2025}
}