compute allocation

Tyler Framework Boosts LLM Reasoning by Up to 14 Points with Smarter Compute Allocation

A new framework called Tyler introduces typed latent reasoning for large language models, learning when to invoke latent computation and how much to allocate. On three backbone LLMs, Tyler improved accuracy by up to 14.49 points over chain-of-thought prompting and up to 4.30 points over competing baselines, while reducing forgetting.