Escarda-VE

Escarda-VE is the vision encoder of the Escarda model family (~39.6M params, 448px / patch16 / 784 tokens). It is the Byrne-VE architecture plus a JEPA head added alongside the HRM refinement block — Escarda's defining family trait.

• ViT-style: RMSNorm, 2D-axial RoPE, QK-Norm, SwiGLU, HRM refinement.
• JEPA head (auxiliary): from a patch token it predicts the raster-order neighbour patch's own representation (stop-gradient target, 1−cosine loss). Zero inference cost.
• Trained by distillation from a frozen DINOv2-base teacher (50k steps, CLS + patch), then 20k steps of DINO-style self-distillation (EMA teacher, cosine prototypes, no collapse).

Escarda-VE vs Byrne-VE (DINOv2 teacher-alignment, n=1024 held-out)

	Byrne-VE	Escarda-VE
Params	39.34M	39.60M (+JEPA head)
CLS cosine	0.776	0.771
PATCH cosine	0.600	0.584
JEPA self-consistency	—	0.040

Read: Escarda trades ~1–3% teacher-alignment (the JEPA objective diverts a little capacity away from pure supervised mimicry) in exchange for a self-supervised spatial neighbour-prediction signal that costs nothing at inference. Same size class as Byrne-VE.

Related

• Byrne-VE — HRM-only sibling
• Escarda-Docling-126M — document VLM built on this encoder
• Escarda-86M-Base