The proposed pipeline reads an input through four stages: edges φ(x), corners ψ(φ), formal parts z(ψ), and class concepts β(z). Each stage factorizes the representation into primitives that can recombine.
Edges φ(x)
Primitive contours extracted from the raw input.
Corners ψ(φ)
Junctions formed by combinations of edges.
Formal Parts z(ψ)
Corner assemblies that describe object components.
Class β(z)
Class concepts composed from formal parts.
Directional extrapolation
Vector Differences in Semantic Space
The proposed shift Δβ = v(Elephant) − v(Horse) defines a direction in semantic embedding space. Projecting that direction is a candidate route into unseen class coordinates.
This is a proposed direction, not evidence on its own that an unseen class will be recognized.
Research Dispatch
Technical updates on compositional generalization and zero-shot learning.