arXiv cs.AIPaper
A*-Thought-V2: Efficient Latent Reasoning via Geometric Dynamics of LLM
The core idea is to prune reasoning steps that wander from the direct question-to-answer path, using geometric alignment in PCA space as a criterion. If your use case is cost-sensitive reasoning or long contexts, this is worth testing. The method is more principled than hard pruning since it preserves deviating steps as compressed latents. Applicable to any CoT workflow where inference cost matters.