Hybrid Reasoning Agents: LLM agents that think in latent space, act through text

	Hybrid Reasoning Agents: LLM agents that think in latent space, act through text(arxiv.org)
	503 points by allinonai 7 days ago \| 236 comments
	tl;dr: HybridAgents combine latent-space reasoning with text-based tool use, switching between modes via a lightweight "HybridLink" module and a continuous working memory that preserves context across turns. The system is trained with two tailored methods—HybridSFT for stable hybrid generation and HybridRL for learning when to think latently vs. act in text. Across 11 benchmarks, it reportedly beats frontier LLM agents by 10.4% while cutting tokens 35-55%, running 1.8-2.6x faster, and reducing costs 2.7-3.7x.
	HN Discussion: ↓Latent reasoning raises safety/interpretability concerns and was previously avoided by labs for alignment reasons ↓The model fails in practice, getting stuck in reasoning loops on simple tasks •Questions how this approach differs from or improves on existing latent reasoning architectures ~Suggests technical improvements like running latent reasoning concurrently with text generation ↓Objects to conflating agents with reasoning; reasoning should remain the LLM's role