TST — Token Superposition Training

### TL;DR

Nous Research unveiled Token Superposition Training (TST), a technique claiming 2.5x faster LLM training times by optimizing how models process redundant data sequences. TST works by superimposing tokens during training to reduce compute on repetitive patterns, with zero architectural changes required to the final deployed model.

Key Insights & Metrics

Key Features

• 2.5x faster LLM pretraining with no changes to the final model architecture
• Token superposition reduces compute on redundant sequence patterns
• Compatible with standard transformer architectures and training pipelines

Discussion