Latent Reasoning in TRMs is Secretly a Policy Improvement Operator

Understand

Recently, small models with latent recursion have obtained promising results on complex reasoning tasks.

• These results are typically explained by the theory that such recursion increases a networks depth, allowing it to compactly emulate the capacity of larger models.
• However, the performance of recursively added layers remains behind the capabilities of one pass models with the same feed-forward depth.
• This means that in the looped version, not every recursive step effectively contributes to depth.