Hybrid Reasoning Agents
How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and interact through text, while latent reasoning offers an efficient internal medium but lacks native tool access and reasoning transparency. We bridge these two directions with Hybrid Reasoning Agents (HybridAgents), which dynamica
Reading in Plain English mode — toggle below to switch
How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and interact through text, while latent reasoning offers an efficient internal medium but lacks native tool access and reasoning transparency. We bridge these two directions with Hybrid Reasoning Agents (HybridAgents), which dynamica
This paper introduces a novel approach to agent design, bridging the gap between human-understandable text-based reasoning and efficient, internal latent reasoning. For ML engineers, understanding HybridAgents is crucial for building more robust, transparent, and capable AI systems that can leverage both symbolic and sub-symbolic thought processes, leading to more advanced agentic applications.