Sep-Latent compresses reasoning to 5.4 tokens

Sep-Latent makes latent reasoning more practical by replacing fixed-length hidden deliberation with adaptive, structurally grounded compression—but its evidence is still concentrated in one benchmark.

• –Separator tokens act as semantic anchors for preserving compressed reasoning state
• –Adaptive termination allocates more latent computation to harder queries
• –Multi-level distillation helps align explicit reasoning traces with the latent pathway
• –The 5.4-token average suggests meaningful inference-efficiency gains over verbose chain-of-thought
• –Broader testing is needed across models, tasks, latency, and failure modes