---
title: "Who cites Hunyuan-DiT: A Powerful — 34 citing papers"
description: "34 papers of the Elamur Research library cite «Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese…"
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# Who cites «Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding»

34 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding»](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuan-dit-powerful-multi/)

1. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models arXiv:2412.03603**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 169 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
2. [**Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling arXiv:2501.17811**Xiaokang Chen, Zhiyu Wu, Xingchao Liu, et al.*2025 · 112 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-janus-pro-unified-multimodal/)
3. [**Qwen-Image Technical Report arXiv:2508.02324**Chenfei Wu, Jiahao Li, Jingren Zhou, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-qwen-image-technical-report/)
4. **[JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ma-2024-janusflow-harmonizing-autoregression-rectified/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Yiyang Ma, Xingchao Liu, Xiaokang Chen, et al.*2024 · 52 citations*
5. [**Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model arXiv:2502.10248**Guoqing Ma, Haoyang Huang, Kun Yan, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/ma-2025-step-video-t2v-technical/)
6. [**HunyuanImage 3.0 Technical Report arXiv:2509.23951**Tencent Hunyuan Foundation Model Team*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuanimage-3-0-technical/)
7. [**Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation arXiv:2501.12202**Zibo Zhao, Zeqiang Lai, Qingxiang Lin, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-hunyuan3d-2-0-scaling/)
8. **[UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision](https://md.research.elamur.ai/free/en/papers/fang-2026-unicorn-self-improving-unified-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Fang, Ruiyan Han, XinYu Sun, et al.*2026 · 11 citations*
9. [**Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model arXiv:2503.07703**Lixue Gong, Xiaoxia Hou, Fanshi Li, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/gong-2025-seedream-2-0-native/)
10. **[UniCM: A Unified Consistency Model For Efficient Multimodal Generation and Understanding](https://md.research.elamur.ai/free/en/papers/xu-2026-unicm-unified-consistency-model-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenkai Xu, Xu Wang, Zhenyi Liao, et al.*2026*

24 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuan-dit-powerful-multi/) — Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding