{"work":{"id":"fde63b0b-25e7-43d9-9867-7d6a2ba6d710","openalex_id":"https://openalex.org/W4396945138","doi":"10.48550/arxiv.2405.08748","arxiv_id":"2405.08748","raw_key":null,"title":"Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding","authors":null,"authors_text":"Zhimin Li, Jianwei Zhang, Qin Lin, Jiangfeng Xiong, Yanxin Long, Xinchi Deng","year":2024,"venue":"cs.CV","abstract":"We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transformer structure, text encoder, and positional encoding. We also build from scratch a whole data pipeline to update and evaluate data for iterative model optimization. For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images. Finally, Hunyuan-DiT can perform multi-turn multimodal dialogue with users, generating and refining images according to the context. Through our holistic human evaluation protocol with more than 50 professional human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image generation compared with other open-source models. Code and pretrained models are publicly available at github.com/Tencent/HunyuanDiT","external_url":"https://arxiv.org/abs/2405.08748","cited_by_count":1,"metadata_source":"pith","metadata_fetched_at":"2026-08-05T02:28:24.338817+00:00","pith_arxiv_id":"2405.08748","created_at":"2026-05-09T03:04:47.631695+00:00","updated_at":"2026-08-05T02:28:24.338817+00:00","title_quality_ok":true,"display_title":"Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding","render_title":"Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding"},"hub":{"state":{"work_id":"fde63b0b-25e7-43d9-9867-7d6a2ba6d710","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":42,"external_cited_by_count":1,"distinct_field_count":6,"first_pith_cited_at":"2024-09-27T16:06:11+00:00","last_pith_cited_at":"2026-06-22T17:53:26+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-23T22:59:24.201492+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":6},{"context_role":"baseline","n":4},{"context_role":"dataset","n":1}],"polarity_counts":[{"context_polarity":"background","n":6},{"context_polarity":"baseline","n":4},{"context_polarity":"use_dataset","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}