arXiv (All)
open access
Tokenizer-Generator Coupling in Medical Image Generation
Latent medical image generators usually treat the tokenizer as fixed preprocessing. We test whether this separation holds in a controlled ChestMNIST study at $64\times64$ that crosses discrete tokenizers, generator families, and sampler settings under a shared latent grid, with continuous-latent ref
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
- CompDiff enables fair and zero shot medical image generation across demographic intersections through compositional diffusion#1129202
- Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval#974486
- Binding Multiple Modalities via Multimodal Wasserstein Barycenter#1118873
- GenRouter: Unified Workflow Routing for Agentic Image Generation#625282
- GenRouter: Unified Workflow Routing for Agentic Image Generation#623009
Record · ID 1118681
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