{"work":{"id":"6f58ba2c-1c9d-47c8-bc8b-c6ae6636971d","openalex_id":null,"doi":null,"arxiv_id":"2402.13929","raw_key":null,"title":"SDXL-Lightning: Progressive Adversarial Diffusion Distillation","authors":null,"authors_text":"Shanchuan Lin, Anran Wang, Xiao Yang","year":2024,"venue":"cs.CV","abstract":"We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL. Our method combines progressive and adversarial distillation to achieve a balance between quality and mode coverage. In this paper, we discuss the theoretical analysis, discriminator design, model formulation, and training techniques. We open-source our distilled SDXL-Lightning models both as LoRA and full UNet weights.","external_url":"https://arxiv.org/abs/2402.13929","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-05-25T05:10:22.052590+00:00","pith_arxiv_id":"2402.13929","created_at":"2026-05-10T02:48:27.424378+00:00","updated_at":"2026-06-05T21:23:00.469572+00:00","title_quality_ok":true,"display_title":"SDXL-Lightning: Progressive Adversarial Diffusion Distillation","render_title":"SDXL-Lightning: Progressive Adversarial Diffusion Distillation"},"hub":{"state":{"work_id":"6f58ba2c-1c9d-47c8-bc8b-c6ae6636971d","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":24,"external_cited_by_count":null,"distinct_field_count":3,"first_pith_cited_at":"2025-04-28T03:42:42+00:00","last_pith_cited_at":"2026-05-22T12:20:46+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":"2026-06-10T16:56:50.976833+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":4},{"context_role":"baseline","n":3},{"context_role":"method","n":1}],"polarity_counts":[{"context_polarity":"background","n":4},{"context_polarity":"baseline","n":3},{"context_polarity":"use_method","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}