  Neural implicit fields are quickly emerging as an attractive representation
for learning based techniques. However, adopting them for 3D shape modeling and
editing is challenging. We introduce a method for $\mathbf{E}$diting
$\mathbf{I}$mplicit $\mathbf{S}$hapes $\mathbf{T}$hrough $\mathbf{P}$art
$\mathbf{A}$ware $\mathbf{G}$enera$\mathbf{T}$ion, permuted in short as
SPAGHETTI. Our architecture allows for manipulation of implicit shapes by means
of transforming, interpolating and combining shape segments together, without
requiring explicit part supervision. SPAGHETTI disentangles shape part
representation into extrinsic and intrinsic geometric information. This
characteristic enables a generative framework with part-level control. The
modeling capabilities of SPAGHETTI are demonstrated using an interactive
graphical interface, where users can directly edit neural implicit shapes.
