Next-Latent Prediction Transformers [R]

Short summary

Microsoft Research introduces NextLat, a self-supervised method that trains transformers to predict their own latent states instead of just the next token. This approach improves representation learning and enables 3.3x faster inference through self-speculative decoding. Code and research paper are available on GitHub and arXiv.

• •NextLat teaches transformers to form compact world models by predicting latent state transitions
• •Achieves 3.3x faster inference via recursive multi-step lookahead in latent space
• •Improves data efficiency through denser supervision compared to next-token prediction alone

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