Adversarial unpaired representation translation (vec2vec)

Learns a map between two embedding spaces with no paired correspondence at all — via GAN-style adversarial training on both outputs and latents plus a Vector Space Preservation (VSP) loss that explicitly matches pairwise inner products (Gram matrices) between input and translated embeddings — turning cross-model geometric convergence into a constructive, unsupervised translation.