Conceptio › Archive › arXiv (OAI Expanded)
arXiv (OAI Expanded) open access

A Latent Distribution Perspective on Evaluating and Improving Latent Generative Models

Fang, Xianghong et al.
arXiv (OAI Expanded) · Papers
Open Source ↗Direct PDF ↓
computer-vision-and-pattern-recognition
In latent generative models, reconstruction quality is often assumed to correlate with generative performance. However, reconstruction FID (rFID) can exhibit weak or even negative correlation with generation FID (gFID). We attribute this misalignment to a latent distribution mismatch: reconstruction
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

Record · ID 1393798
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