calm-continuous-autoregressive-language-models

Replace discrete token prediction with continuous vector prediction by training a high-fidelity autoencoder to compress K tokens into single latent vectors, enabling K-fold sequence length reduction while maintaining likelihood-free generation through energy-based scoring rules.

Independent GitHub snapshot · Automated classification · Original documentation governs