Artificial Intelligence #large language models#ai
Latent Thought Flow: Efficient Reasoning in LLMs Cuts Cost and Boosts Accuracy
Researchers propose Latent Thought Flow (LTF), a method that models LLM reasoning as continuous trajectories in latent space, using GFlowNet and entropy-weighted objectives. LTF outperforms explicit Chain-of-Thought and latent reasoning baselines, achieving 9.5% higher accuracy while cutting reasoning length by 27.2%, addressing the linguistic bottleneck that inflates inference costs.
Jun 16, 2026 1 source