arXiv (All)
open access
Multimodal Conditioning of Fine-Tuned Stable Diffusion XL for Controllable and Culturally Faithful Ulos Motif Generation
The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manually driven design methods. This study proposes a multimodal generative framework integrating a fine-tuned Latent Diffusion Model (Stable Diffusion XL
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes#926679
- Theoretical Framework, Technical Evolution, and Future Prospects of Cross-Modal Mapping and Controllable Image Generation Under Multi-Source Heterogeneous Collaboration.#232137
- LoSATok: Low-Dimensional Semantic-Acoustic Tokenizer for Cross-Domain Audio Understanding and Generation#1070837
- NeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation#1011424
- Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions#271764
Record · ID 1011698
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive