Driftline is an independent research effort studying structural reliability in generative diffusion systems.
The project focuses on how generated images can appear visually plausible while still failing basic structural or anatomical logic. Current work emphasizes controlled prompt testing, repeatable review workflows, and failure-pattern analysis across object classes.
- structural correctness in generated images
- prompt variation under controlled conditions
- repeatable visual evaluation workflows
- recurring failure patterns in generative models
- the gap between visual plausibility and structural correctness
Structural Stability Failures in Diffusion Image Models
A scored observational note examining chair-generation failures under minimal prompt conditions.
https://driftline-us.ai/papers/driftline_research_note_001.pdf
Hand Prompt Comparisons and Structural Reliability in Diffusion Image Models
A structured hand-family comparison examining how constrained prompt variations affect structural correctness in diffusion-generated hands, with emphasis on the difference between improved plausibility and actual anatomical reliability.