Babel: Visual Language Emergence

Can a visual language emerge from scratch rather than being designed in advance? Visual representations today are built on fixed, human-designed languages, from SVG to plotting libraries to domain-specific languages. The choice of language determines the available abstractions and the size of the search space, yet the language itself is rarely questioned. We introduce Babel, a bi-level framework in which an outer loop evolves primitive operations from expressiveness gaps while an inner loop generates visualizations with the current language. Starting from only four geometric primitives, Babel proposes, validates, and refines primitives over a scheduled stream of tasks. As gaps close, valid updates decline and growth saturates only when one registry is shared across tasks. Crucially, what emerges are mechanisms rather than policies: primitives compress repeated execution without taking task-specific decisions away from the caller. On a benchmark spanning six scientific visualization domains, the emerged language expresses the same figures in $4.06\times$ fewer calls than its seed basis and $1.67\times$ fewer than a hand-crafted DSL, at quality indistinguishable from both and from free-form Python. Its primitives also transfer across domains at no cost in quality, suggesting that what emerges is a general drawing language rather than domain-specific shortcuts. These results show that the representation space itself can be optimized during task solving, with reusable mechanism-level abstractions emerging from the task distribution.